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Staff Software Engineer(MLOps)

Toast · Bangalore

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R & D : Engineering : Fintech Data Science & AI Bangalore, India Posted May 8, 2026

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

Now, more than ever, the Toast team is committed to our customers. We’re taking steps to help restaurants navigate these unprecedented times with technology, resources, and community. Our focus is on building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that we’ll deliver on their needs for today while investing in experiences that will power their restaurant of the future.

Bready* to make a change?

Toast is looking for a Staff Machine Learning Engineer to serve as a technical linchpin for our AI Platform team. At the P4 level, you aren't just deploying models; you are designing the fundamental infrastructure that enables dozens of teams to build, deploy, and monitor AI at scale. You will act as a force multiplier, mentoring senior engineers and setting the architectural standards for our MLOps lifecycle—from feature stores and automated retraining to high-performance inference at the edge.

About this Roll*:

Architectural Leadership: Design and lead the evolution of a unified MLOps platform that supports diverse needs across Toast, ensuring high availability, scalability, and security of ML services.
Engineering Excellence: Champion and institutionalize best practices for CI/CD for ML (MLOps), automated testing, and infrastructure-as-code (Terraform).
Cross-Functional Synergy: Lead collaborative efforts across Data Engineering, DevOps, and Product teams to bridge the gap between model prototyping and production-grade reliability.
Strategic Roadmapping: Partner with leadership and Product Managers to define the 1-2 year technical vision for AI infrastructure, prioritizing long-term stability over short-term fixes.
Operational Ownership: Set the standard for observability and incident response for ML systems, driving root-cause analysis for complex system failures.
Mentorship: Actively mentor P2 and P3 engineers, fostering a culture of technical rigor and continuous learning.

Do you have the right ingredients*?

Education: Bachelor’s or Master’s degree in Computer Science, AI, or a related technical field.
Experience: A minimum of 10-12+ years of professional software engineering experience, with at least 6-7 years specifically focused on productionizing and scaling ML systems at the enterprise level.
Core Tech Stack: Expert-level proficiency in Python, Scala, or Java/Kotlin. Extensive experience with PySpark and high-performance computing.
Generative AI & LLMOps: Proven track record of taking LLM applications from research to production, including experience with Vector Databases, LangChain/LangGraph, and A2A protocols.
System Design: Superior ability to design distributed systems that handle millions of requests with sub-second latency.
Experience with microservice based architecture, preferably with AWS tooling (SageMaker, DynamoDB, Athena, Glue, etc.)
Experience in software engineering best practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration, MLflow
Profound knowledge of model deployment, orchestration (Apache airflow, Prefect), scaling, and managing CPU/GPU resources efficiently.
Exceptional problem-solving, analytical skills and the ability to tackle complex problems with a critical thinking approach.
Outstanding communication and interpersonal skills, coupled with a demonstrated ability to work collaboratively within a team environment.
Foundational knowledge in statistical concepts (e.g. classification, regression, etc) and deep learning algorithms (e.g. CNN, RNN) is desirable

Bonus Ingredients (The "Staff" Edge)

Data Strategy: Experience implementing enterprise-grade Feature Stores (e.g., Tecton, Feast) and real-time streaming frameworks like Apache Flink or Ray.
Full-Stack Visibility: Ability to dive into the UI/UX layer (React) or deep into the kernel/networking layer to debug performance bottlenecks.

Open Source/Community: Contributions to relevant open-source projects (MLflow, Kubeflow, etc.) or a history of speaking at industry conferences.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

How Toast Uses AI in its Hiring Process

Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. To learn more: https://careers.toasttab.com/ai-in-hiring

Diversity, Equity, and Inclusion is Baked into our Recipe for Success

At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences.

We Thrive Together

We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the restaurant community. To learn more about how we work globally and regionally, check out: https://careers.toasttab.com/locations-toast.

Apply today!

Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidateaccommodations@toasttab.com.

------

For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Ready to apply?

Apply to Toast

Toast

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Sr. Analytics Engineer- Hybrid in Bangalore

Smartsheet · Bangalore, INDIA

Apply now

Business Intelligence & Ops India Posted May 7, 2026

For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday.

Smartsheet is hiring a Senior Analytics Engineer to lead the way in data-driven decision-making. You will be responsible for the creation and maintenance of a governed, reliable, and scalable analytics system, transforming raw data into usable datasets for DS/ML, analytics, and reporting.

A key aspect of this role is leading the architecture and implementation of efficient data transformation systems within Snowflake, fostering data democratization and impacting business outcomes. Working closely with BI analysts and Data scientists, you will ensure data accessibility and drive activation on critical customer-facing platforms.

This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India.

You Will:

Leading the implementation of efficient and scalable systems that optimize data transformations from our data lake in Snowflake into clean, documented data products.
Contribute to the design standards and architectural principle standards, designs and processes.
Build and maintain a governed, robust, reliable, and scalable analytics system (DW/DV).
Collaborating with BI analysts and data scientists to provide proper data accessibility guidelines.
Foster data democratization via activation of data on critical platforms like Smartsheet platform, Amplitude, Thoughtspot , Gainsight.
Create and contribute to frameworks that improve data quality and observability to identify and resolve issues faster.
Create and implement data testing plans, encompassing data validation, data quality assessment, and regression testing, to identify anomalies, inconsistencies, or errors in produced datasets.
Mentor and guide teams and help drive high standards across the team by conducting design reviews and engineering ideation forums.
Collaborate with cross-functional teams to assess data privacy needs and define data masking strategies aligned with industry compliance standards (e.g., GDPR, HIPAA, CCPA).

You Have:

6+ years of experience in advanced data modeling using Data Vault (DV 2.0), dbt, and Snowflake.
Proven experience in building analytics systems with data transformation, dependency, and workload management (Data Vault, AutomateDV, dbt core, Airflow, Snowflake, GitLab, SQL).
Proven experience with building and maintaining business analytics layers and semantic layers to enable self-service for non-technical end-users.
Strong production experience supporting and maintaining analytics/data warehouse solutions with mission-critical datasets.
Familiarity with data governance principles for maintaining datasets to enable a single source of truth.
Familiarity with self-serve product analytics tools (Amplitude, Thoughtspot, Tableau, Gainsight, etc.).
Knowledge of code management and CI/CD practices (GitLab, Airflow, Snowflake, Terraform).
Familiarity with AWS solutions such as S3, EC2, VPC.

Get to Know Us:

At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.

Equal Opportunity Employer:

Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.

If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

#LI-Remote

Ready to apply?

Smartsheet

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Principal Analytics Engineer (Data Architect) - Hybrid in Bangalore

Smartsheet · Bangalore, INDIA

Apply now

Business Intelligence & Ops India Posted May 7, 2026

For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday.

As a global leader in Collaborative Work Management and with a market cap of $10bn we’ve experienced incredible growth in EMEA, expanding from 1 team and 3 engineers in 2018 to 9 teams with over 70 engineers in 2024. As we expand into India and build out a new operation, we're searching for a talented and motivated Principal Analytics Engineer (Data Architect) to serve as a thought leader in our data-driven decision-making. You will be responsible for the end-to-end system design and architecture of our business critical analytical systems (DWs). This role will be responsible for the design and development of a governed, reliable, and scalable analytics ecosystem, transforming raw data into high-value, performant data products for DS/ML, analytics, and reporting.

A key aspect of this role is providing thought leadership and architecting efficient, large-scale data transformation systems within Snowflake. You will have demonstrated experience architecting data solutions for SaaS companies, specifically within the Go-To-Market (GTM), Marketing, Customer Experience, and Financial business domains. Working as a strategic advisor to BI analysts, Data Scientists, and business leadership, you will drive the organization's data strategy, ensure data accessibility, and foster data democratization across the enterprise.

This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India.

You Will:

Lead the end-to-end system design and architecture for large, complex analytics systems, optimizing data transformations from our data lake in Snowflake into analytical data products (DWs).
Define and drive the adoption of design standards, architectural principles, and data modeling methodologies (including Data Vault (DV 2.0) and dimensional modeling) across the organization.
Propose and drive strategic initiatives and coordinate the technical roadmap for analytical systems across the engineering organization partnering closely with the Big Data Platforms (BDP) team.
Serve as the data architect for critical SaaS business domains, including Go-To-Market, Marketing, Customer Experience, and Finance, translating ambiguous business problems into scalable technical analytical solutions.
Develop and implement the organization's data strategy for data quality, observability, and testing, raising the bar for engineering quality.
Architect and guide teams to build and maintain a governed, robust, reliable, and scalable analytics system leveraging Gen AI capabilities including AI-assisted code development practices.
Act as a trusted advisor to BI analysts, data scientists, and business leaders, educating and advising leadership on technical data topics and data accessibility strategies.
Foster data democratization via activation of data on critical platforms like Smartsheet Platform, Amplitude, ThoughtSpot, Gainsight & Salesforce.
Actively mentor analytics engineers and provide mentorship across disciplines, leading forums such as guilds, design reviews, and engineering forums.
Collaborate with cross-functional teams to assess data privacy needs and define data masking strategies aligned with industry compliance standards (e.g., GDPR, HIPAA, CCPA).

You Have:

12+ years of experience in advanced data modeling, data architecture, and data warehousing. This role is expected to do development activities in combination of the data architecture scope, so hands-on experience is necessary.
Deep expertise and 10+ years of hands-on experience with Data Vault (DV 2.0) and Dimensional Modeling.
Expert-level knowledge of modern data stacks, including Snowflake, dbt, and data orchestration tools (e.g., Airflow, GitLab pipelines).
Proven experience architecting and building analytical products for SaaS companies in GTM, Marketing, Customer Experience, and Financial data domains.
Comprehensive understanding of data topologies (e.g., data mesh, hub/spoke) and data modeling methodologies (e.g., Data Vault, Kimball, Inmon).
Demonstrated ability to drive clarity in ambiguous environments where the strategy may not be defined.
Proven experience with building and maintaining business analytics layers and semantic layers to enable self-service for non-technical end-users.
Strong production experience supporting and maintaining analytics/data warehouse solutions with mission-critical datasets.
Exceptional communication skills, with experience educating and advising senior leadership and mentoring teams across disciplines.
Strong knowledge of data governance principles, CI/CD practices (e.g., GitLab), self-serve analytics tools (e.g., Amplitude, ThoughtSpot), and cloud architectures (AWS preferred).

Get to Know Us:

At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.

Equal Opportunity Employer:

Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.

If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

#LI-Remote

Ready to apply?

Smartsheet

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Sr. Revenue Operations Data Engineer (Hybrid in Bangalore)

Smartsheet · Bangalore, INDIA

Apply now

GTM Ops Analytics India Posted May 7, 2026

For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday.

Smartsheet is looking for an experienced Data Engineer to support and accelerate the productivity of our Go-To Market organization. In this role, you will work with Data Engineers to help build scalable and reliable data and reporting infrastructure. You will partner with Analytics decision-makers as part of a collaborative, motivated team. Your work will be instrumental in helping our Sales partners optimize their pipeline, increase retention, and close deals.

Our ideal candidate is curious and displays an ability to translate abstract data requests into actionable data solutions . To be successful in this role, you are able to communicate to a diverse audience of internal stakeholders. You should have strong technical acumen with data analytics tools and languages, the ability to identify areas of opportunity within the business, and build innovative solutions.

You Will:

Help to create, evolve, and maintain the reporting infrastructure for the Sales organization to facilitate data across the organization
Partner with engineering, data science, and other analytics teams to build scalable analytics solutions with a focus on reporting capabilities
Mine large datasets to ensure data accuracy and completeness for reporting purposes
Analyze and monitor data for anomalies, with a focus on data quality and consistency within reports
Develop and maintain key performance indicators (KPIs) to track sales performance, pipeline health, and other critical metrics
Automate report generation and distribution to improve efficiency
Provide technical expertise and guidance to junior analysts on data extraction, transformation, and loading (ETL) processes and reporting best practices
Ensure data governance and data integrity across all reporting tools and platforms
Proactively identify and propose improvements to existing reporting processes and systems
Be a mentor and leader to the more junior analysts on the team
Perform other duties as assigned

You Have:

Bachelor's degree in a quantitative field (e.g. engineering, sciences, math, statistics, business, or economics)
5+ years of experience in an analytics/engineering role with increasing responsibility
Experience in Cloud and SaaS go-to-market (GTM)
Expertise in SQL and preparing data for analysis, modeling, and visualization
3+ years of experience using Python for data analysis / automation
3+ years of experience with dbt core
3+ years of experience with Git (Gitlab, Github etc.) and CI/CD concepts like branching, merging, Code Reviews etc.
Demonstrated experience with a modern engineering tech stack (Airflow, AWS, Docker etc.)
Experience working with a business intelligence tool like Tableau, PowerBI, Looker, etc.

Nice To Have:

Experience building ML models
Proficiency with Tableau preferred
Experience with statistics (time series analysis, cluster analysis, multivariate analysis)
Experience publishing and presenting data and findings to executives and non-data users

Get to Know Us:

At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.

Equal Opportunity Employer:

Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.

If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

#LI-Remote

Ready to apply?

Smartsheet

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Principal Data Engineer / Architect - Individual Contributor

Smartsheet · Bangalore, INDIA

Apply now

Engineering - Developers India Posted May 7, 2026

For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday.

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Principal Data & AI/ML Ops Engineers, who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

Data Architecture and Design: Designing and overseeing the architecture of scalable and reliable data platforms, including data pipelines, storage solutions, and processing systems
Data Modelling and Management:Developing and implementing data models, ensuring data quality, and establishing data governance policies
Data Pipeline Development: Building and optimising data pipelines for ingesting, processing, and transforming large datasets from various sources
Performance Optimisation: Identifying and resolving performance bottlenecks in data pipelines and systems, ensuring efficient data retrieval and processing
Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
Data Security and Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
Perform other duties as assigned

You Have:

Enterprise SaaS software solutions with high availability and scalability
Solution handling large scale structured and unstructured data from varied data sources
Experience in building and maintaining data platform systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure ensuring scalability, reliability, efficiency and security
Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
In depth experience in System design involving large Petabytes of data with Databricks Lakehouse
Experience in modern AI/Data infrastructure patterns, Semantics layer Organizing data for AI agents (metadata, context)
AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
Programming languages like Python, SQL, and potentially Java or Scala
Exposure to Snowflake and Data pipeline frameworks like Airbyte/Airflow is preferable
Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
Solution Cost Optimisations and design to cost
Driving engineering excellence initiatives
Legally eligible to work in India on an ongoing basis

Get to Know Us:

At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.

Equal Opportunity Employer:

Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.

If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

#LI-Remote

Ready to apply?

Smartsheet

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Senior Analyst, Model Risk Management

Toast · Bangalore, India

Apply now

G & A : Compliance Bangalore, India Posted May 7, 2026

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

As Senior Analyst in our Model Risk Management team, you will help manage the Model Risk Program including completing model validation reviews, maintaining the model risk inventory, and monitoring model performance particularly for Fraud and Gen AI Models. You will work closely with the Data Science Team, architects, engineers and product managers to assess the risk of model design, implementation, and use across product lines.

A day in the life (Responsibilities)

Support the implementation and day-to-day execution of the Second Line of Defense (2LOD) Model Risk Management (MRM) program for high-risk models, with particular focus on Fraud detection models (Transaction Fraud & Merchant Fraud) and Generative AI / LLM-based systems deployed across Toast.
Assist in maintaining and enhancing the Model Risk Management framework, including policies, procedures, validation standards, governance documentation, templates, and best practices aligned with evolving regulatory and industry expectations.
Enforce model lifecycle standards across development, implementation, use, monitoring, recalibration, change management, governance, and decommissioning, ensuring appropriate controls for traditional ML models as well as GenAI systems (e.g., RAG architectures, copilots, AI-assisted decision tools).
Contribute to the development, risk-tiering, and ongoing maintenance of a comprehensive model inventory, including assessment of model impact, intrinsic risk (complexity and methodology), reliance on model outputs, and emerging AI-specific risks.
Perform independent model validation reviews under the guidance of senior leadership, covering conceptual soundness, data integrity, model methodology, performance metrics (e.g., AUC, precision/recall, calibration), stability, bias/fairness risk, explainability, and monitoring frameworks. Produce validation reports and track issue remediation plans through closure.
For Fraud models, evaluate class imbalance handling, threshold optimization, cost-sensitive performance metrics, operational overlays, rule-based controls, and portfolio-level impact analyses.
For Generative AI systems, validate systems and evaluate risks related to hallucination, prompt injection, adversarial vulnerabilities, data privacy and leakage, model explainability limitations, bias, guardrails, output monitoring, jailbreak testing, regression testing, and human-in-the-loop controls.
Partner with Data Science, Data Engineering, Product/Engineering, Information Security, Legal/Compliance, Finance, Credit Risk and Business teams to obtain documentation, perform effective challenge, conduct validation and oversee performance monitoring
Prepare reports and executive materials summarizing model risk issues, validation findings, monitoring insights, and remediation status for leadership review, risk committees, audit committees, and internal audit engagements.
Research and stay informed on industry developments in fraud analytics, machine learning, Generative AI governance, and regulatory guidance (e.g., SR 11-7, OCC 2011-12, NIST AI RMF). Propose enhancements to strengthen Toast’s Model Risk and AI Governance framework.
Contribute to the development of model risk training materials and support delivery of training sessions to key stakeholders to enhance awareness of fraud model risk and AI-related risks.
Support ad-hoc initiatives related to model risk governance, AI oversight, regulatory compliance, and enterprise risk management enhancements.

What you'll need to thrive (Requirements)

Advanced degree in Data Science, Statistics, Applied Mathematics, Computer Science, Engineering, or a related quantitative discipline
5+ years of relevant industry experience in Model Risk Management, Model Validation, Data Science, or Machine Learning within fintech, banking, payments, technology, or consulting environments, with exposure to fraud analytics, credit risk, or AI/ML model governance.
Strong understanding of machine learning methodologies and statistical foundations, including model development, validation techniques, performance evaluation, calibration, and stability analysis.
Hands-on experience with fraud detection models (e.g., transaction monitoring, chargeback prediction, merchant risk scoring) and familiarity with concepts such as class imbalance handling, threshold optimization, precision/recall trade-offs, and cost-sensitive evaluation.
Familiarity with Generative AI and LLM-based systems (e.g., RAG architectures, embeddings, prompt engineering, AI copilots) and awareness of associated risks such as hallucination, bias, prompt injection, and data leakage.
Strong proficiency in Python and SQL; experience with data science and ML tools such as Spark, scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Familiarity with software engineering best practices (version control, CI/CD, testing frameworks, Airflow, AWS or cloud platforms) is a plus.
Knowledge of model risk management frameworks and regulatory guidance (e.g., SR 11-7, OCC 2011-12) and familiarity with emerging AI governance frameworks (e.g., NIST AI RMF) is highly desirable.
Ability to translate complex quantitative methodologies into clear business insights and effectively challenge first-line model development teams while maintaining strong cross-functional partnerships.
Demonstrated critical thinking, analytical rigor, and structured problem-solving skills, with the ability to manage multiple priorities and deliver high-quality outputs under tight deadlines.
Excellent written and verbal communication skills, including experience drafting formal validation reports, executive summaries, and committee-level materials.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy

We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

How Toast Uses AI in its Hiring Process

Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. To learn more: https://careers.toasttab.com/ai-in-hiring

Diversity, Equity, and Inclusion is Baked into our Recipe for Success

At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences.

We Thrive Together

We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the restaurant community. To learn more about how we work globally and regionally, check out: https://careers.toasttab.com/locations-toast.

Apply today!

Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidateaccommodations@toasttab.com.

------

For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Ready to apply?

Apply to Toast

Toast

View all jobs →

Senior Staff Software Engineer ( Machine learning Platform)

Tekion · Bengaluru, Karnataka, India

Apply now

Engineering Bangalore HQ Posted May 7, 2026

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

Why This Role Matters

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.

What Makes This Opportunity Unique

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue. You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models .

Responsibilities

Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking.

Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics).

Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction.

Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning.

Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval.

Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows.

Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging.

Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance.

Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems.

Evolve the domain graph and entity resolution; build reliable data ingestion pipelines.

Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage.

Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost.

Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity.

Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls.

Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed.

Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices.

Desired Skills & Experience

12–15+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems).

Production experience with Python plus one of Java/Scala/Go; microservices and API design.

MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka).

Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS.

Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows.

Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting.

Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry.

Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns.

Preferred Mindset

Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs.

Thinks in systems - observability, fallback, access control are core, not afterthoughts.

Passionate about AI - enjoys enabling real-world LLM and agentic use cases.

Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation.

Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience.

Documentation and teaching: you make complex systems understandable; you uplevel teams.

Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.

For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

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AI Engineer

ChargePoint · Bengaluru, Karnataka, India

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2504 - NOC IN-Karnataka-Bangalore Posted May 7, 2026

About Us

With electric vehicles expected to be nearly 30% of new vehicle sales by 2025 and more than 50% by 2040, electric mobility is becoming a reality. ChargePoint (NYSE: CHPT) is at the center of this revolution, powering one of the world’s leading EV charging networks and a comprehensive set of hardware, software and mobile solutions for every charging need across North America and Europe. We bring together drivers, businesses, automakers, policymakers, utilities and other stakeholders to make e-mobility a global reality.

Since our founding in 2007, ChargePoint has focused solely on making the transition to electric easy for businesses, fleets and drivers. ChargePoint offers a once-in-a-lifetime opportunity to create an all-electric future and a trillion-dollar market.

At ChargePoint, we foster a positive and productive work environment by committing to live our values of Be Courageous, Charge Together, Love our Customers, Operate with Openness, and Relentlessly Pursue Awesome. These values guide how we show up every day, align, and work together to build a brighter future for all of us.

Join the team that is building the EV charging industry and make your mark on how people and goods will get everywhere they need to go, in any context, for generations to come.

Reports To

Director, NOC Delivery & Automation

What You Will Be Doing

Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)
Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

8+ years of software engineering experience with 4+ years focused on AI/ML systems in production
Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
Background in computer vision, image processing, or visual transformer architectures
Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
Experience working with massive datasets (50TB+) and building scalable data pipelines
Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
Familiarity with RLHF-style preference tuning and model alignment techniques
Experience with observability and monitoring stacks including metrics, logging, and tracing
Certifications in Generative AI, Agentic AI, or related specialization.

Location

Bangalore, India

We are committed to an inclusive and diverse team. ChargePoint is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

If there is a match between your experiences/skills and the Company needs, we will contact you directly.

ChargePoint is committed to fostering an inclusive workplace that welcomes and supports all qualified individuals. In alignment with this commitment, we ensure that persons with disabilities are provided with reasonable accommodations throughout the employment process.

If you need a reasonable accommodation to participate in the application or interview process, to perform essential job functions, or to access any other benefits and privileges of employment, please contact us at accommodations@chargepoint.com.

ChargePoint is an equal opportunity employer.
Applicants only - Recruiting agencies do not contact.

Ready to apply?

ChargePoint

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Senior Data and Analytics Engineer

Everpure · Bangalore, India

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Finance Office - India (Bangalore - 1 Sobha) Posted May 6, 2026

We’re in an unbelievably exciting area of tech and are fundamentally reshaping the data storage industry. Here, you lead with innovative thinking, grow along with us, and join the smartest team in the industry.

This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us.

THE ROLE

We are seeking a highly skilled and hands-on Senior Finance Data & Analytics Engineer (IC role) to lead the design and development of the Finance Data Cube, enabling enterprise-wide insights into Customer Lifetime Value (CLTV), Contribution Margin, and other key financial metrics.

WHAT YOU'LL DO

Design, build, and own the Finance Data Cube, integrating financial, customer, and operational datasets.
Model data to support CLTV, Contribution Margin, and other profitability KPIs across multiple dimensions (customer, product, LOB, geography, etc.)
Be a data architect for Finance , bring different data into cohesive and answer critical questions
Leverage AI tools to automate data summarization, anomaly detection, and narrative insights for Finance stakeholders.
Scale data infrastructure to support large volumes and complex financial models.
Build and manage Semantic Layer models to standardize business metrics and enable self-serve analytics
Translate complex financial concepts and KPIs into scalable, maintainable data models.
Implement strong controls for data quality, lineage, and governance.
Maintain clear documentation of data transformations, metric definitions, and AI model logic.
We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

Experience: 8+ years in Finance Data Engineering, FP&A Analytics, or Financial Systems, with exposure to AI/ML-based analytics(added advantage)
Proficiency with Snowflake and modern data stacks with strong SQl and data modeling expertise
Deep understanding of finance data set , SAP , Contribution margin, CLTV would be an added advantage
Experience with data orchestration tools (Airflow, dbt) and tableau platform
Hands-on experience with Python, PySpark, or R for automation and model integration.
Proven ability to translate financial logic into scalable data models.
Experience in Cortex Analyst/Search components to enable AI/ML-driven insights, natural language querying, and intelligent data discovery is preferred.
Knowledge of predictive modeling, time-series forecasting, and generative AI in analytics.
Ability to evaluate and apply AI responsibly in financial contexts.

#LI-ONSITE

WHAT YOU CAN EXPECT FROM US:

Innovation: We celebrate those who think critically, like a challenge, and aspire to be trailblazers.
Growth: We give you the space and support to grow along with us and to contribute to something meaningful. We have been named Fortune's Best Workplaces in Technology™, Fortune's Best Workplaces in the Bay Area™, and certified as a Great Place to Work®!
Team: We build each other up and set aside ego for the greater good.

And because we understand the value of bringing your full and best self to work, we offer a variety of perks to manage a healthy balance, including flexible time off, wellness resources, and company-sponsored team events. Check out purebenefits.com for more information.

ACCOMMODATIONS AND ACCESSIBILITY:

Candidates with disabilities may request accommodations for all aspects of our hiring process. For more on this, contact us at TA-Ops@purestorage.com if you’re invited to an interview.

OUR COMMITMENT TO A STRONG AND INCLUSIVE TEAM:

We’re forging a future where everyone finds their rightful place and where every voice matters. Where uniqueness isn’t just accepted but embraced. That’s why we are committed to fostering the growth and development of every person, cultivating a sense of community through our Employee Resource Groups and advocating for inclusive leadership.

Everpure is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other characteristic legally protected by the laws of the jurisdiction in which you are being considered for hire.

Join us and bring your best.

Bring your bold.

Pure and simple.

Ready to apply?

Apply to Everpure

Everpure

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Senior AI Engineer

Reltio · Bangalore

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Technology India Posted May 6, 2026

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

About the Role

We are seeking a Senior AI Engineer with a strong foundation in Python capabilities, and hands-on experience building Agentic AI applications that integrate with Large Language Models (LLMs) Large Language Models (LLMs). We are also looking for him to be a full-stack Engineer with hands-on experience with mobile front-end hands-on experience with mobile front-end Flutter, React-native. This role blends traditional backend engineering expertise with next-generation AI agentic systems development, requiring not just system design skills, but also creativity in prompt engineering, AI product development and working with data-rich environments.

You will contribute to the design and implementation of intelligent backend services that coordinate LLMs, agents, and data workflows to support enterprise-grade agentic systems.

Key Responsibilities

Develop robust, scalable Java/Python based backend systems that enable the orchestration of Agentic AI workflows.
Develop state-of-the-art AI/ML models for solving real-world data management challenges such as entity resolution, classification, similarity matching, and anomaly detection.
Integrate LLMs (e.g., OpenAI, Mistral, Claude, LLaMA) into backend pipelines to power autonomous or semi-autonomous decision-making.
Hands on experience with mobile front-end Flutter, React-native etc.
Develop scalable ML workflows using Spark, MLlib, PyTorch, TensorFlow, or MLFlow, with seamless integration into production systems.
Translate business needs into technical design and collaborate with data scientists, product managers, and platform engineers to operationalize models.
Work closely with various stakeholders to design agent architectures and LLM toolchains (using frameworks like LangGraph, Crew AI, AutoGen, etc.).
Implement services and APIs that manage prompt chaining, tool invocation, and contextual memory for agents.
Collaborate with data engineers to ensure clean, efficient, and real-time access to structured and semi-structured data.
Apply prompt engineering best practices to improve agent behavior, task accuracy, and adaptability.
Monitor and optimize service performance, reliability, and scalability in production environments.
Continuously monitor and improve model performance using feedback loops, A/B testing, drift detection, and retraining strategies.
Contribute to code reviews, mentoring, and best practices for hybrid backend/AI development.

Required Qualifications

5+ years of overall experience mobile front-end Flutter, React-native etc
2+ years of experience in developing and deploying machine learning models and AI products in production environments.
Experience in Agentic AI systems development using tools such as LangGraph, Crew AI, AutoGen, or similar.
Proficiency in Python (NumPy, scikit-learn, pandas, PyTorch/TensorFlow) and experience with large-scale data processing tools (Spark, Kafka, Airflow).
Experience integrating or orchestrating LLMs within business workflows or intelligent assistants.
Solid understanding of prompt engineering techniques (e.g., system messages, chaining, tool invocation prompts).
Familiarity with data engineering concepts, including pipelines, data models, and ETL workflows.
Strong grasp of object-oriented design, data structures, and algorithms.

Preferred Qualifications

Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, RAG pipelines).
Background in building microservices or backend systems for data-rich AI/ML platforms.
Experience with vector databases, embedding services, or semantic search integration.
Knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and DevOps best practices.
Experience in developing LLM-powered agents, copilots, or task bots.

What We Offer

Opportunity to work on cutting-edge backend and AI systems, including agentic automation and LLM innovation.
A flexible hybrid work model in our Bangalore office.
Competitive compensation with performance-based rewards.
A culture that promotes engineering excellence, experimentation, and growth.Access to learning platforms, technical workshops, and industry-leading AI research.

Why Join Reltio?*

Health & Wellness:
- Comprehensive Group medical insurance including your parents with additional top-up options.
- Accidental Insurance
- Life insurance
- Free online unlimited doctor consultations
- An Employee Assistance Program (EAP)
Work-Life Balance:
- 36 annual leaves, which includes Sick leaves – 18, Earned Leaves - 18
- 26 weeks of maternity leave, 15 days of paternity leave
- Very unique to Reltio - 01 week of additional off as recharge week every year globally
Support for home office setup:
- Home office setup allowance.
Stay Connected, Work Flexibly: Mobile & Internet Reimbursement
No need to pack a lunch—we’ve got you covered with a free meal.And many more…..

Reltio is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Reltio is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities.

Ready to apply?

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Reltio

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Staff AI Engineer

ChargePoint · Bengaluru, Karnataka, India

Apply now

2504 - NOC IN-Karnataka-Bangalore Posted May 6, 2026

About Us

With electric vehicles expected to be nearly 30% of new vehicle sales by 2025 and more than 50% by 2040, electric mobility is becoming a reality. ChargePoint (NYSE: CHPT) is at the center of this revolution, powering one of the world’s leading EV charging networks and a comprehensive set of hardware, software and mobile solutions for every charging need across North America and Europe. We bring together drivers, businesses, automakers, policymakers, utilities and other stakeholders to make e-mobility a global reality.

Since our founding in 2007, ChargePoint has focused solely on making the transition to electric easy for businesses, fleets and drivers. ChargePoint offers a once-in-a-lifetime opportunity to create an all-electric future and a trillion-dollar market.

At ChargePoint, we foster a positive and productive work environment by committing to live our values of Be Courageous, Charge Together, Love our Customers, Operate with Openness, and Relentlessly Pursue Awesome. These values guide how we show up every day, align, and work together to build a brighter future for all of us.

Join the team that is building the EV charging industry and make your mark on how people and goods will get everywhere they need to go, in any context, for generations to come.

Reports To

Director, NOC Delivery & Automation

What You Will Be Doing

Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)
Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

8+ years of software engineering experience with 4+ years focused on AI/ML systems in production
Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
Background in computer vision, image processing, or visual transformer architectures
Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
Experience working with massive datasets (50TB+) and building scalable data pipelines
Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
Familiarity with RLHF-style preference tuning and model alignment techniques
Experience with observability and monitoring stacks including metrics, logging, and tracing
Certifications in Generative AI, Agentic AI, or related specialization.

Location

Bangalore, India

We are committed to an inclusive and diverse team. ChargePoint is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

If there is a match between your experiences/skills and the Company needs, we will contact you directly.

ChargePoint is committed to fostering an inclusive workplace that welcomes and supports all qualified individuals. In alignment with this commitment, we ensure that persons with disabilities are provided with reasonable accommodations throughout the employment process.

If you need a reasonable accommodation to participate in the application or interview process, to perform essential job functions, or to access any other benefits and privileges of employment, please contact us at accommodations@chargepoint.com.

ChargePoint is an equal opportunity employer.
Applicants only - Recruiting agencies do not contact.

Ready to apply?

ChargePoint

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Senior Data Engineer, Guest & Host

Airbnb · Bangalore, India

Apply now

Software Engineering Bangalore, India Posted May 6, 2026

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join:

The Guest & Host team based out of India, operates to ensure high quality supply and merchandising differentiates our brand, by providing tools to be used by 1000+ operations agents for supply vetting and quality moderation. As Airbnb expands beyond the core, it is looking to onboard supply outside of the core stays business which requires enhancing our tools. The operational tasks we face are diverse and rapidly evolving. The current manual processes and lack of optimum tooling capabilities hinder the ability of operation agents to work more efficiently, maintain business continuity, and achieve higher scale.

The Difference You Will Make:

As a Data Engineer on the Guest & Host team, you will play a pivotal role in shaping the systems that onboard and manage the highest quality supply across Airbnb. You’ll build robust data pipelines and platforms that power end-to-end visibility for supply operations, from onboarding and regulatory compliance to AI-assisted vetting and listing quality enforcement. Your work will directly enable operations, product, and ML teams to scale trusted supply globally, ensuring every home, service, and experience meets Airbnb’s standards. Whether it’s surfacing insights to optimize onboarding flows, enabling smarter audit triggers, or supporting nuanced licensing workflows, your contributions will be foundational to helping hosts join Airbnb efficiently and ensuring guests have access to safe, high-quality stays.
As you build and maintain key components of the critical data ecosystem, you’ll have the opportunity to contribute to creating standards and best practices for Airbnb’s Data Engineering. Your work on solving complex business challenges at scale will be instrumental in shaping the tools, processes, and standards used by the broader data community.

A Typical Day:

Design, build, and maintain robust and efficient data pipelines that collect, process, and store data from various sources, including user interactions, listing details, and external data feeds.
Develop data models that enable the efficient analysis and manipulation of data for merchandising optimization. Ensure data quality, consistency, and accuracy.
Build scalable data pipelines (SparkSQL & Scala) leveraging Airflow scheduler/executor framework
Collaborate with cross-functional teams, including Data Scientists, Product Managers, andSoftware Engineers, to define data requirements, and deliver data solutions that drive merchandising and sales improvements.
Contribute to the broader Data Engineering community at Airbnb to influence tooling and standards to improve culture and productivity
Improve code and data quality by leveraging and contributing to internal tools to automatically detect and mitigate issues

Your Expertise:

6+ years of relevant industry experience
BE/B.tech in computer science or relevant technical field
Extensive experience designing, building, and operating robust distributed data platforms (e.g., Spark, Kafka, Flink, HBase) and handling data at the petabyte scale.
Strong knowledge of Java, Scala, or Python, and expertise with data processing technologies and query authoring (SQL).
Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions
Expertise with ETL schedulers such as Apache Airflow, Luigi, Oozie, AWS Glue or similar frameworks
Solid understanding of data warehousing concepts and hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)
Excellent written and verbal communication skills

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range shown below is annualized, is inclusive of allowances and is subject to change and may be modified in the future. This role may also be eligible for bonus or incentives, one or more equity programs, benefits, and Employee Travel Credits.

India Annual Pay Range

₹4,500,000—₹6,500,000 INR

Ready to apply?

Apply to Airbnb

Airbnb

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Senior AI Engineer

ChargePoint · Bengaluru, Karnataka, India

Apply now

2504 - NOC IN-Karnataka-Bangalore Posted May 5, 2026

About Us

With electric vehicles expected to be nearly 30% of new vehicle sales by 2025 and more than 50% by 2040, electric mobility is becoming a reality. ChargePoint (NYSE: CHPT) is at the center of this revolution, powering one of the world’s leading EV charging networks and a comprehensive set of hardware, software and mobile solutions for every charging need across North America and Europe. We bring together drivers, businesses, automakers, policymakers, utilities and other stakeholders to make e-mobility a global reality.

Since our founding in 2007, ChargePoint has focused solely on making the transition to electric easy for businesses, fleets and drivers. ChargePoint offers a once-in-a-lifetime opportunity to create an all-electric future and a trillion-dollar market.

At ChargePoint, we foster a positive and productive work environment by committing to live our values of Be Courageous, Charge Together, Love our Customers, Operate with Openness, and Relentlessly Pursue Awesome. These values guide how we show up every day, align, and work together to build a brighter future for all of us.

Join the team that is building the EV charging industry and make your mark on how people and goods will get everywhere they need to go, in any context, for generations to come.

Reports To

Director, NOC Delivery & Automation

What You Will Be Doing

Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)
Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

6+ years of software engineering experience with 4+ years focused on AI/ML systems in production
Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
Background in computer vision, image processing, or visual transformer architectures
Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
Experience working with massive datasets (50TB+) and building scalable data pipelines
Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
Familiarity with RLHF-style preference tuning and model alignment techniques
Experience with observability and monitoring stacks including metrics, logging, and tracing
Certifications in Generative AI, Agentic AI, or related specialization.

Location

Bangalore, India

We are committed to an inclusive and diverse team. ChargePoint is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

If there is a match between your experiences/skills and the Company needs, we will contact you directly.

ChargePoint is committed to fostering an inclusive workplace that welcomes and supports all qualified individuals. In alignment with this commitment, we ensure that persons with disabilities are provided with reasonable accommodations throughout the employment process.

If you need a reasonable accommodation to participate in the application or interview process, to perform essential job functions, or to access any other benefits and privileges of employment, please contact us at accommodations@chargepoint.com.

ChargePoint is an equal opportunity employer.
Applicants only - Recruiting agencies do not contact.

Ready to apply?

ChargePoint

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Senior AI Engineer

ChargePoint · Bengaluru, Karnataka, India

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2504 - NOC IN-Karnataka-Bangalore Posted May 5, 2026

About Us

With electric vehicles expected to be nearly 30% of new vehicle sales by 2025 and more than 50% by 2040, electric mobility is becoming a reality. ChargePoint (NYSE: CHPT) is at the center of this revolution, powering one of the world’s leading EV charging networks and a comprehensive set of hardware, software and mobile solutions for every charging need across North America and Europe. We bring together drivers, businesses, automakers, policymakers, utilities and other stakeholders to make e-mobility a global reality.

Since our founding in 2007, ChargePoint has focused solely on making the transition to electric easy for businesses, fleets and drivers. ChargePoint offers a once-in-a-lifetime opportunity to create an all-electric future and a trillion-dollar market.

At ChargePoint, we foster a positive and productive work environment by committing to live our values of Be Courageous, Charge Together, Love our Customers, Operate with Openness, and Relentlessly Pursue Awesome. These values guide how we show up every day, align, and work together to build a brighter future for all of us.

Join the team that is building the EV charging industry and make your mark on how people and goods will get everywhere they need to go, in any context, for generations to come.

Reports To

Director, NOC Delivery & Automation

What You Will Be Doing

Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)
Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

8+ years of software engineering experience with 4+ years focused on AI/ML systems in production
Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
Background in computer vision, image processing, or visual transformer architectures
Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
Experience working with massive datasets (50TB+) and building scalable data pipelines
Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
Familiarity with RLHF-style preference tuning and model alignment techniques
Experience with observability and monitoring stacks including metrics, logging, and tracing
Certifications in Generative AI, Agentic AI, or related specialization.

Location

Bangalore, India

We are committed to an inclusive and diverse team. ChargePoint is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

If there is a match between your experiences/skills and the Company needs, we will contact you directly.

ChargePoint is committed to fostering an inclusive workplace that welcomes and supports all qualified individuals. In alignment with this commitment, we ensure that persons with disabilities are provided with reasonable accommodations throughout the employment process.

If you need a reasonable accommodation to participate in the application or interview process, to perform essential job functions, or to access any other benefits and privileges of employment, please contact us at accommodations@chargepoint.com.

ChargePoint is an equal opportunity employer.
Applicants only - Recruiting agencies do not contact.

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ChargePoint

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GE

Staff Data Software Engineer

Get Well Network · Bangalore

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Engineering & AI- Get Well Network Get Well Network - Bangalore Posted May 4, 2026

Opportunity

Get Well is seeking an experienced and highly motivated Staff Data Software Engineer to help build and optimize our cloud-native data platform that powers AI, analytics, and clinical applications. You will play a key role in developing scalable, compliant data infrastructure and pipelines designed specifically for the healthcare domain, while mentoring junior engineers and leading cross-functional initiatives to drive innovation.

This is a hands-on engineering role suitable for someone who thrives at the intersection of modern data engineering, cloud-native platforms, DevOps, healthcare data, and AI enablement. Candidates must have hands-on software development experience with at least one healthcare company—preferably in the provider space—with exposure to EHRs and core healthcare data domains.

Responsibilities

Data Engineering & Platform Development

Design, build, and maintain scalable data pipelines supporting batch and real-time use cases.
Develop and maintain production-grade data workflows that move and transform sensitive healthcare data across distributed systems at scale.
Work with Spark, Databricks, Airflow/Temporal, and dbt to ingest, process, and manage structured and unstructured data.
Design and implement reusable, efficient data models for analytics and AI/ML use cases.
Ensure platform resiliency using CI/CD pipelines, observability tools, and logging frameworks.
Leverage Infrastructure as Code practices using Terraform, CloudFormation, or equivalent to manage cloud resources.

Healthcare Data Integration & Compliance

Ingest and normalize complex healthcare data sets (FHIR, HL7, CCDA, Claims, EDI, Epic/Clarity, etc.).
Familiarity with clinical coding systems and ontologies, such as ICD-10, SNOMED CT, LOINC, or RxNorm.
Collaborate with compliance and security teams to ensure adherence to HIPAA, GDPR, and internal controls.
Implement fine-grained access control, encryption at rest and in transit, audit logging, and data lineage strategies.

AI & GenAI Enablement

Work alongside AI/ML and data science teams to build pipelines feeding predictive and generative models.
Tune data infrastructure for performance across distributed systems and hybrid data stores like SQL, MongoDB, ClickHouse.
Prioritize scalability and flexibility in designing LLM-compatible pipelines and use GenAI best practices for healthcare use cases.
Utilize Spark clusters and query frameworks such as SparkSQL and SPARQL for large-scale data access.
Utilize and manage graph databases (e.g., Neo4j, Amazon Neptune, or similar) to support complex relationship modeling and healthcare data connectivity use cases.
Enable high-quality training data pipelines and implement feature stores and model serving systems.

Data Governance, Quality & Monitoring

Implement data quality frameworks and establish robust validation processes using tools such as Great Expectations or equivalent.
Build automated anomaly detection tools for data drift and integrity checks.
Support data cataloging, metadata management, and ensure consistent documentation across datasets.

Collaboration, Mentorship & Leadership

Act as a mentor to junior engineers through code reviews, paired programming, and technical guidance.
Lead cross-functional projects with teams including clinical informatics, architecture, security, product, and design.
Contribute to and enforce data engineering best practices, patterns, and platform standardization.

Learning and Innovation

Research and evaluate emerging tools and frameworks (e.g., Apache Iceberg, Delta Lake) for incorporation into the platform.
Proactively identify opportunities to improve architecture and leverage evolving trends in GenAI and cloud-native computing.

Qualifications

Education & Experience

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
8–12 years of experience in software or data engineering roles including at least 3 years working with large-scale or cloud-native data systems.
Must have prior software development experience in the healthcare domain—including payers, providers, health tech, medical devices, or life sciences.
Functional knowledge and direct experience with healthcare data types (FHIR, HL7, Claims, EDI, Epic/Clarity, etc.).
Demonstrated experience in designing, implementing, and maintaining data pipelines that move and transform healthcare data with production-level quality, reliability, and performance.

Technical Skills

Advanced programming experience in Python, SQL, and distributed processing with Apache Spark.
Cloud-native platform experience with Azure.
Proven capability with Infrastructure as Code (Terraform, CloudFormation) strongly preferred.
Experience with data warehouses and lakes including Snowflake, Databricks, and ClickHouse.
Familiarity working with GenAI tools and ML pipelines in production environments.
Strong skills in data modeling, job orchestration (Airflow), data transformation (dbt), and pipeline optimization.
Experience with DevOps/tooling stacks for CI/CD, containerization, observability, and cost optimization.
Familiarity with data validation and anomaly detection tools such as Great Expectations.
Experience with SparkSQL and SPARQL is a plus.

Professional Attributes

Excellent communication and collaboration skills across cross-functional, domain, and technical stakeholders.
Ability to lead initiatives and drive data engineering standards.
Self-driven, with a commitment to delivering high-quality solutions in regulated and sensitive environments.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

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GE

Get Well Network

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Data Analyst III

ZoomInfo Technologies LLC · Bengaluru, Karnataka, India

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913 Engineering - Data Ops Bangalore, India Posted Apr 30, 2026

ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen–fast.

At ZoomInfo we encourage creativity, value innovation, demand teamwork, expect accountability and cherish results. If you are collaborative, take initiative, and get stuff done we want to talk to you! We have high aspirations for the company and are looking for the right people to help fulfil the dream. We strive to continually improve every aspect of the company and use cutting-edge technologies and processes to delight our customers and rapidly increase revenue.

Role Overview: ZoomInfo is seeking a Data Analyst III to join the Data Operations and Analysis team. This role partners closely with Product, Engineering, and Research teams to enhance data infrastructure, improve data quality, and deliver actionable insights that drive business impact.

Key Responsibilities:

Develop a deep understanding of data systems, pipelines, and infrastructure.
Analyze current data processes, identify gaps, and recommend scalable improvements.
Drive initiatives to enhance data accuracy, coverage, and efficiency.
Collaborate cross-functionally with Data Engineering, Product, and Research teams.
Perform advanced data analysis and present insights in a clear, structured manner.
Mentor junior analysts and contribute to team capability building.
Work independently to explore data, propose solutions, and execute projects end-to-end.

Core Competencies:

Strong analytical thinking and problem-solving ability.
Ability to work in ambiguous environments and drive clarity.
Effective communication with both technical and non-technical stakeholders.
High attention to detail and strong organizational skills.
Self-driven with the ability to manage multiple priorities.

Required Qualifications:

5+ years of experience in analytics, data operations, or quantitative research.
Advanced proficiency in SQL, Python, BigQuery, and Excel.
Strong understanding of ETL processes and data quality challenges.
Experience working with large-scale datasets.
Familiarity with AI/ML concepts including NLP and data modeling.

Preferred Qualifications:

Experience building or deploying AI/ML solutions.
Exposure to tools like Tableau or Looker Studio.
Experience with Databricks, AWS, or Airflow.
Background in product-driven or project-based environments.

Impact: This role plays a critical part in shaping the future of ZoomInfo’s data ecosystem by improving data reliability, scalability, and strategic value.

#LI-SG2

#LI-Hybrid

About us:

ZoomInfo (NASDAQ: GTM) is the Go-To-Market Intelligence Platform that empowers businesses to grow faster with AI-ready insights, trusted data, and advanced automation. Its solutions provide more than 35,000 companies worldwide with a complete view of their customers, making every seller their best seller.

ZoomInfo is committed to protecting your privacy when you apply for jobs with us. Please review our Job Applicant Privacy Notice for more details on how we handle your personal information.

ZoomInfo may use a software-based assessment as part of the recruitment process. More information about this tool, including the results of the most recent bias audit, is available here.

ZoomInfo is proud to be an equal opportunity employer, hiring based on qualifications, merit, and business needs, and does not discriminate based on protected status. We welcome all applicants and are committed to providing equal employment opportunities regardless of sex, race, age, color, national origin, sexual orientation, gender identity, marital status, disability status, religion, protected military or veteran status, medical condition, or any other characteristic protected by applicable law. We also consider qualified candidates with criminal histories in accordance with legal requirements.

For Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. ZoomInfo does not administer lie detector tests to applicants in any location.

Ready to apply?

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ZoomInfo Technologies LLC

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Data Engineer

Definitive Healthcare, India · Bengaluru, Karnataka, India

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Product & Engineering Bangalore, India Posted Apr 29, 2026

Analytical Wizards is part of the Definitive Healthcare family. We balance innovation with an open, friendly culture and the backing of a long-established parent company, known for its ethical reputation. We guide customers from what’s now to what’s next by unlocking the value of their data and applications to solve their challenges, achieving outcomes that benefit both business and society. Our people are our biggest asset, they drive our innovation advantage and we strive to offer a flexible and collaborative workplace where they can thrive. We offer industry-leading benefits packages to promote a creative and inclusive culture. If driving real change gives you a sense of pride and you are passionate about powering social good, we’d love to hear from you.

Job Description – Data Engineer

About the Role

We are looking for a candidate who is passionate about building scalable data pipelines, optimizing data workflows, and ensuring high data quality across systems. Candidates should demonstrate strong technical foundations, the ability to work independently, and a willingness to collaborate in a dynamic environment.

Core Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines to support business and analytical needs.
Work extensively with Databricks, Python, and PySpark to process large datasets.
Build and manage DAGs using Apache Airflow for workflow orchestration.
Collaborate with cross-functional teams to understand data requirements and translate them into efficient engineering solutions.
Develop and optimize complex SQL queries and participate in data modeling activities for relational and cloud data warehouses.
Work with Amazon S3 for data storage, ingestion, partitioning, and integration within broader data lake and pipeline ecosystems.
Ensure high standards of data quality, reliability, and performance across all data processes.
Contribute to documentation, best practices, and continuous improvement initiatives.

Core Technical Requirements

Python Programming

Strong experience writing clean, efficient Python code for data manipulation, automation, scripting, and ETL workflows.
Familiarity with widely used data libraries (e.g., pandas, numpy).

Databricks

Hands-on experience with Databricks for distributed data processing.
Proficiency in PySpark, Delta Lake, notebooks, and building scalable pipelines.

Orchestration Tools

Apache Airflow (Required): Ability to design, implement, and maintain complex DAGs for scheduling and orchestrating workflows.
Argo Workflows (Preferred): Experience with Kubernetes-native orchestration platforms is an added advantage.

SQL Skills

Advanced SQL expertise including writing complex queries, query optimization, and working with relational/cloud data warehouses.
Experience in data modeling and performance tuning.

Cloud Storage (Amazon S3)

Practical knowledge of S3 for ingestion, storage, data partitioning, access control, and integration as part of data lake architectures.

Experience Level

2–5 years in Data Engineering or related roles..

Preferred Personal Attributes

Strong analytical and problem-solving skills.
Excellent communication and collaboration abilities.
Ability to work in a fast-paced, evolving environment.

Ready to apply?

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Definitive Healthcare, India

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DevOps Engineer

Definitive Healthcare, India · Bengaluru, Karnataka, India

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Commercial Bangalore, India Posted Apr 29, 2026

Analytical Wizards is part of the Definitive Healthcare family. We balance innovation with an open, friendly culture and the backing of a long-established parent company, known for its ethical reputation. We guide customers from what’s now to what’s next by unlocking the value of their data and applications to solve their challenges, achieving outcomes that benefit both business and society. Our people are our biggest asset, they drive our innovation advantage and we strive to offer a flexible and collaborative workplace where they can thrive. We offer industry-leading benefits packages to promote a creative and inclusive culture. If driving real change gives you a sense of pride and you are passionate about powering social good, we’d love to hear from you.

Designation :DevOps Engineer
Location: Bangalore
Work Mode: Hybrid
Experience Required: 2–4 years

Job Summary

We are looking for a Professional Services OPS Engineer to support client-facing data
operations and workflow execution. This role focuses on job monitoring, issue resolution,
data sharing, and operational support across multiple platforms to ensure reliable and
timely client deliverables.

Key Responsibilities

• Monitor and troubleshoot job failures in Visual Cron, Argo, and Databricks
• Perform root-cause analysis and implement fixes to maintain workflow stability
• Build, schedule, and maintain workflows using Visual Cron, Argo, Databricks Jobs, and
Snowflake Tasks
• Manage data sharing and deliveries via Databricks Share, Snowflake Share, S3, and SFTP
• Push MDE and non-MDE data to client environments post job success
• Support monthly refresh cycles, reruns, backfills, and ad-hoc operational requests
• Handle client and internal PS inquiries related to deliverables and missing files
• Collaborate with internal teams to improve operational processes

Required Skills

• Hands-on experience with job schedulers (Visual Cron preferred)
• Argo or Airflow workflow orchestration
• Strong working knowledge of Databricks
• SQL for data validation and troubleshooting
• Python for scripting and automation
• Basic knowledge of S3
• Experience with SFTP-based data deliveries

Good to Have

• Snowflake Tasks and Snowflake Share
• Azure Blob Storage Exposure and Experience supporting client-facing or production systems.

Ready to apply?

Apply to Definitive Healthcare, India

Definitive Healthcare, India

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Senior Software Engineer - Backend - Multi Product Platform

Abnormal · Hybrid - Bangalore, India

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Multi-Product Platform Hybrid - Bangalore, India Posted Apr 28, 2026

About the Role

At Abnormal AI, we are on a thrilling mission to safeguard the world's largest enterprises against a vast range of relentless email and collaboration application cyber security attacks. Our relentless pursuit involves crafting an exceptional suite of products that empowers customers to seamlessly visualize, expertly control, and fearlessly combat cyber-security threats.

The MPP organization in Abnormal AI owns the product platform which enables scalable product development to support the business to create and launch various enterprise-level products for the customers with consistent experience. We are looking for a Sr Software Engineer who will be a feature lead for the Configuration Platform team under the MPP organisation. Our Configuration Platform team is creating a unified, intelligent system that empowers engineers to ship faster and build better. You'll architect solutions that set new standards for developer productivity, making configurations a competitive advantage. Join us to create an infrastructure that scales with our ambitious growth and directly impacts how we deliver exceptional products to our customers.

What You’ll Do

Technical Delivery & Operational Excellence

Build and iterate on product offerings, APIs, platforms, frameworks and tools.
Responsible for designing, developing, and maintaining feature buildouts to support a world-class user experience for our customers.
Ensure system stability and reliability of your crafted work.
Participate in regular code and design reviews as well as team-wide on-call rotation.
Write code with testability, readability, edge cases, and errors in mind.
Write and review technical design documents.

Teamwork & Collaboration

Communicate effectively in an asynchronous manner with team members to provide updates, discuss challenges and propose solutions.
Collaborate closely with product managers, designers, and engineers to ensure seamless integration and effective development.
Take ownership of projects and is a driver who adds instant adrenaline and drives positive impact when placed on projects and teams.
Participate in team roadmap discussions & (good to have) propose long-term plans.
Actively contribute to knowledge sharing within the team and participate in professional development activities.

Must have Skills

Experienced Sr Software Engineer having 7+ years of industry experience with strong software engineering fundamentals.
Experience in building low-latency and high-throughput systems.
Futuristic, the ability to look at the bigger picture, and the growing system needs.
Growth-oriented, looking to increase impact, responsibility, and ownership over time
Proven ability to own and drive complex systems end-to-end, with strong knowledge of team-owned services and the ability to collaborate and influence cross-team goals and roadmaps.
Strong experience writing production Python and Golang code and working with SQL and NoSQL databases.
Solid experience in system design and building resilient, scalable applications with an emphasis on operational excellence.
Detail-driven and care about code quality, testing, and performance.
Ability to make practical trade-offs and propose technical solutions, including writing technical design documents and leading their adoption.
Strong understanding of service health, monitoring, fault tolerance, and incident response practices.
Strong communication skills and proven ability to work autonomously and asynchronously with remote collaborators and stakeholders.
Strong communication and mentorship skills to influence team-wide engineering practices.

Nice to Have Skills

Experience with Golang and Airflow orchestration.
Platform as a product experience.
Familiarity with ChatGPT, Cursor and other GenAI productivity tools.

#LI-AB2

Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Ready to apply?

Abnormal

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Senior Software Engineer (Tech Lead) - Message Security Detection

Abnormal · Hybrid - Bangalore, India

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Message Security Detection Hybrid - Bangalore, India Posted Apr 28, 2026

What you will do

Architect & Scale: Design and maintain high-throughput detection systems and backend services, ensuring low latency and high reliability.
Data Orchestration: Lead the development of robust data pipelines using Spark and Airflow to supply detection teams with high-fidelity data for ML model training and evaluation.
Technical Leadership: Partner with Engineering Managers to define technical roadmaps, mentor junior/mid-level engineers, and drive best practices in code quality and system design.
AI-Driven Innovation: Lead the team in adopting AI productivity initiatives, leveraging tools like Claude, OpenAI, and GitHub Copilot to accelerate the development lifecycle and automate internal workflows.
Cross-functional Collaboration: Work closely with TPMs, Product Managers, Data Scientists, and Security Researchers to translate complex business needs into scalable technical solutions.
Operational Excellence: Manage and optimize cloud-native infrastructure on AWS/EKS, ensuring systems are cost-effective, secure, and performant.

Must Haves

8+ years of professional experience: Proven track record in production-level backend development with Python or Golang.
Data Engineering Expertise: Expert-level proficiency in building and optimizing distributed data pipelines using Spark and Airflow (or equivalent orchestration tools).
Cloud & Infrastructure: Extensive experience managing and scaling cloud-native applications on AWS (highly preferred), GCP, or Azure, with a proven track record of hands-on container orchestration using EKS.
Leadership & Mentorship: Experience leading technical projects, mentoring engineers, and contributing to the long-term technical strategy of a team.
System Design: Strong ability to design complex integrations and handle significant throughput/latency challenges.
Problem Solving: A methodical approach to performance debugging, benchmarking, and resolving bottlenecks in large-scale systems.
Database Proficiency: Strong experience with Postgres or similar relational databases at scale.
Education: BS in Computer Science, Applied Sciences, or a related engineering field.

Nice to Haves

Frontend Literacy: Familiarity with React and TypeScript to assist with internal tool visualizations.
Data Ecosystems: Experience with Databricks, Snowflake, or similar data lakehouse architectures.
Cybersecurity Domain: Background in threat detection, network security, or fraud prevention.
Advanced Degrees: MS in Computer Science or Electrical Engineering.

#LI-AB2

Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Ready to apply?

Abnormal

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Senior Software Engineer - Backend - Multi-Product Platform (Customer Journey)

Abnormal · Hybrid - Bangalore, India

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Multi-Product Platform Hybrid - Bangalore, India Posted Apr 28, 2026

About the Role

At Abnormal Security, we are on a thrilling mission to safeguard the world's largest enterprises against a vast range of relentless email and collaboration application cyber security attacks. Our relentless pursuit involves crafting an exceptional suite of products that empowers customers to seamlessly visualize, expertly control, and fearlessly combat cyber-security threats.

The MPP organization in Abnormal Security owns the product platform which enables scalable product development to support the business to create and launch various enterprise-level products for the customers with consistent experience. We are looking for a Sr Software Engineer who will be a feature lead for the Customer Journey (CJ) team, which is focused on optimizing how customers onboard and start using Abnormal’s products. You'll help build systems that streamline the onboarding and proof-of-value (POV) experience, reducing manual steps and accelerating time-to-value. This role involves full-stack development, close collaboration with cross-functional teams, and the opportunity to directly impact customer experience from day one.

What You’ll Do

Technical Delivery & Operational Excellence

Build and iterate on product offerings, APIs, platforms, frameworks and tools.
Responsible for designing, developing, and maintaining feature buildouts to support a world-class user experience for our customers.
Ensure system stability and reliability of your crafted work.
Participate in regular code and design reviews as well as team-wide on-call rotation.
Write code with testability, readability, edge cases, and errors in mind.
Write and review technical design documents.

Teamwork & Collaboration

Communicate effectively in Async manner with team members to provide updates, discuss challenges and propose solutions.
Collaborate closely with product managers, designers, and engineers.
Take ownership of projects and is a driver who adds instant adrenaline and drives positive impact when placed on projects and teams.
Participate in team roadmap discussions & (good to have) proposing long term plans.
Actively contribute to knowledge sharing within the team and participate in professional development activities.

Must have Skills

Experienced Sr Software Engineer having 7+ years of industry experience with strong software engineering fundamentals.
Futuristic, ability to look at the bigger picture, growing system needs.
Growth-oriented, looking to increase impact, responsibility, and ownership over time
Proven ability to own and drive complex systems end-to-end, with strong knowledge of team-owned services and the ability to collaborate and influence cross-team goals and roadmaps.
Strong experience writing production Python code and working with Postgres databases.
Solid experience in system design and building resilient, scalable applications with an emphasis on operational excellence.
Detail driven and care about code quality, testing, and performance.
Ability to make practical trade-offs and propose technical solutions, including writing technical design documents and leading its adoption.
Strong understanding of service health, monitoring, fault tolerance, and incident response practices.
Strong communication skills and proven ability to work autonomously and asynchronously with remote collaborators and stakeholders.
Strong communication and mentorship skills to influence team-wide engineering practices.

Nice to Have Skills

Experience with Golang and airflow orchestration.
Familiarity with ChatGPT, Cursor and other GenAI productivity tools.

#LI-AB2

Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Ready to apply?

Abnormal

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Software Engineer 2

Abnormal · Hybrid - Bangalore, India

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Platform & Infrastructure Hybrid - Bangalore, India Posted Apr 28, 2026

About the Role

Abnormal Security is looking for an experienced and driven Platform & Infra software engineer to join the PI team. Join us and help build the platforms that power Abnormal's growth

Observability Platform - Own and evolve the monitoring, metrics, and alerting infrastructure that every engineering team at Abnormal depends on. You'll work across the Prometheus, Chronosphere, and Grafana stack to ensure engineers can see what their systems are doing in real time — building dashboards, managing metric pipelines at scale, operating the PagerDuty alerting pipeline, and driving cost-efficient observability across all production environments (US, EU, and GovCloud).

Your Impact

Own the observability stack (Prometheus, Chronosphere, Grafana, PagerDuty) that every team relies on to detect, diagnose, and resolve production issues — when you make it better, every engineer at Abnormal gets faster.
Design platforms and developer tooling that remove friction — reducing deployment times, simplifying pipeline authoring, and letting product teams focus on building rather than firefighting.
Drive SLAs and SLOs for critical shared infrastructure ensuring the systems behind our products are resilient and cost-efficient.
Your architectural decisions on alerting pipelines and cross-environment deployments will define what products we can build and how quickly we deliver them to customers.

What you will do

Work with the Tech Lead, Engineering Manager, and Product Manager to design, develop, and deliver key platform features — from technical design docs through production rollout
Own features end-to-end: scoping, implementation, testing, deployment, and post-launch monitoring across multiple environments (US, EU, GovCloud)
Take ownership of 1-3 key services within Observability (Prometheus, Chronosphere, Grafana, PagerDuty pipeline) or Data Infra (Airflow, Spark) and be accountable for their reliability, performance, and evolution
Participate in on-call rotations — triage, diagnose, and resolve production issues independently, building deep operational knowledge of the systems you own
Improve system resilience by converting runbooks into automated solutions, refining SLAs/SLOs, and proactively identifying performance bottlenecks and failure modes
Assume ownership of the reliability of everything you build, including comprehensive unit tests, integration testing, and observability instrumentation
Build platforms, tooling, and APIs that make it easier for other engineering teams to ship — whether that's faster pipeline deployments, better dashboards, or simpler alerting configuration
Partner with internal customers (product and engineering teams) to understand their needs and translate them into scalable platform capabilities
Communicate effectively in an async-first, distributed environment — proactively providing updates, discussing challenges, and proposing solutions without prompting
Mentor junior engineers on the team, helping them ramp up on service operations and development practices
Raise the bar of engineering excellence through code reviews, knowledge sharing, design discussions, and contributing to team best practices

Must Haves

Backend Engineering & Distributed Systems (4+ years)
4+ years of hands-on backend engineering experience designing, building, and operating production-grade distributed systems
Strong proficiency in Python — the primary language for Airflow DAGs, platform services, and automation tooling
Working proficiency in Golang — used for high-performance infrastructure components, metric pipelines, and platform services
Experience building systems that process data at scale — whether metric ingestion pipelines, stream/batch processing, or high-throughput API services
Demonstrated experience owning a service or platform end-to-end — from technical design through production deployment, monitoring, and iteration
Comfortable balancing feature development with operational responsibilities: you've shipped features and kept them running reliably at scale
Experience writing technical design documents that articulate trade-offs, propose solutions, and get buy-in from peers and tech leads
Track record of breaking down ambiguous problems into concrete, deliverable milestones
Experience with fault tolerance patterns — retries, circuit breakers, graceful degradation, backpressure — and knowing when to apply each
Proven incident response capability: you've been on-call, diagnosed production issues under pressure, and driven them to resolution
Strong testing discipline — unit tests, integration tests, and an understanding of what to test and how to keep test suites maintainable
Ability to design systems with a forward-looking perspective — thinking about how your architecture handles 10x growth, multi-region deployment, and evolving requirements
Ability to contribute to and influence cross-team technical direction — you're not just implementing specs, you're shaping the solution
Async-first communication excellence — strong written communication skills for design docs, Slack discussions, PR reviews, and status updates across time zones
Proactive communicator — you surface blockers early, share con
Solid understanding of monitoring, alerting, and observability principles — you've instrumented services, set up dashboards, defined SLIs/SLOs, or triaged production incidents using metrics and logs

Nice to Have

Hands-on experience with Prometheus — PromQL queries, recording rules, alerting rules, relabeling configs, and understanding metric cardinality challenges at scale
Experience with Grafana — building dashboards, templating, managing datasources, and creating meaningful visualizations for operational and business metrics
Familiarity with commercial observability platforms like Chronosphere, Datadog, New Relic, or Honeycomb — understanding trade-offs between self-hosted and managed solutions
Experience designing or operating an alerting pipeline — PagerDuty, OpsGenie, or similar — including alert routing, escalation policies, and reducing noise/alert fatigue

Cloud Infrastructure & Kubernetes

Familiarity with AWS services — EC2, ECS, EKS, S3, RDS, IAM, CloudWatch, Lambda, SQS/SNS — and understanding how to architect cost-effective, secure cloud infrastructure
Experience with Kubernetes (K8s) — deploying and operating workloads, understanding pods/services/deployments, Helm charts, and debugging cluster-level issues
Exposure to Infrastructure-as-Code tools — Terraform, Pulumi, or CloudFormation — and understanding the value of declarative infrastructure management
Experience with CI/CD pipelines — GitHub Actions, Jenkins, or similar — and optimizing build/deploy times for platform services

Programming & Framework

Experience with Django or similar Python web frameworks — building APIs, managing migrations, and understanding ORM performance characteristics
Familiarity with gRPC or protobuf for inter-service communication in a microservices architecture

Technical Leadership & Platform Thinking

Experience leading a small team (2-4 engineers) to build a feature or component from scratch — scoping, task breakdown, code reviews, and delivery management
Experience building internal developer platforms or tooling — CLIs, SDKs, self-service portals, or automation that improved developer productivity
Track record of reducing operational toil — automating runbooks

Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

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Senior AI Engineer

Reltio · Bangalore

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Technology India Posted Apr 28, 2026

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

About the Role

We are seeking a Senior Backend Engineer with a strong foundation in Java, solid Python capabilities, and hands-on experience building Agentic AI applications that integrate with Large Language Models (LLMs). This role blends traditional backend engineering expertise with next-generation AI agentic systems development, requiring not just system design skills, but also creativity in prompt engineering, AI product development and working with data-rich environments.

You will contribute to the design and implementation of intelligent backend services that coordinate LLMs, agents, and data workflows to support enterprise-grade agentic systems.

Key Responsibilities

Develop robust, scalable Java/Python based backend systems that enable the orchestration of Agentic AI workflows.
Develop state-of-the-art AI/ML models for solving real-world data management challenges such as entity resolution, classification, similarity matching, and anomaly detection.
Integrate LLMs (e.g., OpenAI, Mistral, Claude, LLaMA) into backend pipelines to power autonomous or semi-autonomous decision-making.
Develop scalable ML workflows using Spark, MLlib, PyTorch, TensorFlow, or MLFlow, with seamless integration into production systems.
Translate business needs into technical design and collaborate with data scientists, product managers, and platform engineers to operationalize models.
Work closely with various stakeholders to design agent architectures and LLM toolchains (using frameworks like LangGraph, Crew AI, AutoGen, etc.).
Implement services and APIs that manage prompt chaining, tool invocation, and contextual memory for agents.
Collaborate with data engineers to ensure clean, efficient, and real-time access to structured and semi-structured data.
Apply prompt engineering best practices to improve agent behavior, task accuracy, and adaptability.
Monitor and optimize service performance, reliability, and scalability in production environments.
Continuously monitor and improve model performance using feedback loops, A/B testing, drift detection, and retraining strategies.
Contribute to code reviews, mentoring, and best practices for hybrid backend/AI development.

Required Qualifications

5+ years of overall experience in backend engineering, with strong proficiency in Java for scalable, distributed systems.
2+ years of experience in developing and deploying machine learning models and AI products in production environments.
Experience in Agentic AI systems development using tools such as LangGraph, Crew AI, AutoGen, or similar.
Proficiency in Python (NumPy, scikit-learn, pandas, PyTorch/TensorFlow) and experience with large-scale data processing tools (Spark, Kafka, Airflow).
Experience integrating or orchestrating LLMs within business workflows or intelligent assistants.
Solid understanding of prompt engineering techniques (e.g., system messages, chaining, tool invocation prompts).
Familiarity with data engineering concepts, including pipelines, data models, and ETL workflows.
Strong grasp of object-oriented design, data structures, and algorithms.

Preferred Qualifications

Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, RAG pipelines).
Background in building microservices or backend systems for data-rich AI/ML platforms.
Experience with vector databases, embedding services, or semantic search integration.
Knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and DevOps best practices.
Experience in developing LLM-powered agents, copilots, or task bots.

What We Offer

Opportunity to work on cutting-edge backend and AI systems, including agentic automation and LLM innovation.
A flexible hybrid work model in our Bangalore office.
Competitive compensation with performance-based rewards.
A culture that promotes engineering excellence, experimentation, and growth.Access to learning platforms, technical workshops, and industry-leading AI research.

Why Join Reltio?*

Health & Wellness:
- Comprehensive Group medical insurance including your parents with additional top-up options.
- Accidental Insurance
- Life insurance
- Free online unlimited doctor consultations
- An Employee Assistance Program (EAP)
Work-Life Balance:
- 36 annual leaves, which includes Sick leaves – 18, Earned Leaves - 18
- 26 weeks of maternity leave, 15 days of paternity leave
- Very unique to Reltio - 01 week of additional off as recharge week every year globally
Support for home office setup:
- Home office setup allowance.
Stay Connected, Work Flexibly: Mobile & Internet Reimbursement
No need to pack a lunch—we’ve got you covered with a free meal.And many more…..

Reltio is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Reltio is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities.

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Site Reliability Engineer - Big Data (7 to 11 years)

PhonePe · Bangalore

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Site Reliability PhonePe Limited Posted Apr 24, 2026

About PhonePe Limited:

Headquartered in India, its flagship product, the PhonePe digital payments app, was launched in Aug 2016. As of April 2025, PhonePe has over 60 Crore (600 Million) registered users and a digital payments acceptance network spread across over 4 Crore (40+ million) merchants. PhonePe also processes over 33 Crore (330+ Million) transactions daily with an Annualized Total Payment Value (TPV) of over INR 150 lakh crore.

PhonePe’s portfolio of businesses includes the distribution of financial products (Insurance, Lending, and Wealth) as well as new consumer tech businesses (Pincode - hyperlocal e-commerce and Indus AppStore Localized App Store for the Android ecosystem) in India, which are aligned with the company’s vision to offer every Indian an equal opportunity to accelerate their progress by unlocking the flow of money and access to services.

Culture:

At PhonePe, we go the extra mile to make sure you can bring your best self to work, Everyday!. And that starts with creating the right environment for you. We empower people and trust them to do the right thing. Here, you own your work from start to finish, right from day one. PhonePe-rs solve complex problems and execute quickly; often building frameworks from scratch. If you’re excited by the idea of building platforms that touch millions, ideating with some of the best minds in the country and executing on your dreams with purpose and speed, join us!

About the Role:

This role is responsible for managing and maintaining complex, distributed big data ecosystems. It ensures the reliability, scalability, and security of large-scale production infrastructure. Key responsibilities include automating processes, optimizing workflows, troubleshooting production issues, and driving system improvements across multiple business verticals.

Roles and Responsibilities:

Manage, maintain, and support incremental changes to Linux/Unix environments.
Lead on-call rotations and incident responses, conducting root cause analysis and driving postmortem processes.
Design and implement automation systems for managing big data infrastructure, including provisioning, scaling, upgrades, and patching clusters.
Troubleshoot and resolve complex production issues while identifying root causes and implementing mitigating strategies.
Design and review scalable and reliable system architectures.
Collaborate with teams to optimize overall system performance.
Enforce security standards across systems and infrastructure.
Set technical direction, drive standardization, and operate independently.
Ensure availability, performance, and scalability of systems and services through proactive monitoring, maintenance, and capacity planning.
Resolve, analyze, and respond to system outages and disruptions and implement measures to prevent similar incidents from recurring.
Develop tools and scripts to automate operational processes, reducing manual workload, increasing efficiency and improving system resilience.
Monitor and optimize system performance and resource usage, identify and address bottlenecks, and implement best practices for performance tuning.
Collaborate with development teams to integrate best practices for reliability, scalability, and performance into the software development lifecycle.
Stay informed of industry technology trends and innovations, and actively contribute to the organization's technology communities.
Develop and enforce SRE best practices and principles.
Align across functional teams on priorities and deliverables.
Drive automation to enhance operational efficiency.

Skills Required:

Over 7 years of experience managing and maintaining distributed big data ecosystems.
Strong expertise in Linux including IP, Iptables, and IPsec.
Proficiency in scripting/programming with languages like Perl, Golang, or Python.
Hands-on experience with the Hadoop stack (HDFS, HBase, Airflow, YARN, Ranger, Kafka, Pinot).
Familiarity with open-source configuration management and deployment tools such as Puppet, Salt, Chef, or Ansible.
Solid understanding of networking, open-source technologies, and related tools.
Excellent communication and collaboration skills.
DevOps tools: Saltstack, Ansible, docker, Git.
SRE Logging and monitoring tools: ELK stack, Grafana, Prometheus, opentsdb, Open Telemetry.

Good to Have:

Experience managing infrastructure on public cloud platforms (AWS, Azure, GCP).
Experience in designing and reviewing system architectures for scalability and reliability.
Experience with observability tools to visualize and alert on system performance.

PhonePe Full Time Employee Benefits (Not applicable for Intern or Contract Roles)

Insurance Benefits - Medical Insurance, Critical Illness Insurance, Accidental Insurance, Life Insurance
Wellness Program - Employee Assistance Program, Onsite Medical Center, Emergency Support System
Parental Support - Maternity Benefit, Paternity Benefit Program, Adoption Assistance Program, Day-care Support Program
Mobility Benefits - Relocation benefits, Transfer Support Policy, Travel Policy
Retirement Benefits - Employee PF Contribution, Flexible PF Contribution, Gratuity, NPS, Leave Encashment
Other Benefits - Higher Education Assistance, Car Lease, Salary Advance Policy

Our inclusive culture promotes individual expression, creativity, innovation, and achievement and in turn helps us better understand and serve our customers. We see ourselves as a place for intellectual curiosity, ideas and debates, where diverse perspectives lead to deeper understanding and better quality results. PhonePe is an equal opportunity employer and is committed to treating all its employees and job applicants equally; regardless of gender, sexual preference, religion, race, color or disability. If you have a disability or special need that requires assistance or reasonable accommodation, during the application and hiring process, including support for the interview or onboarding process, please fill out this form.

Read more about PhonePe on our blog.

Life at PhonePe

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Senior DevOps Engineer

Get Well Network · Bengaluru, Karnataka, India

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Engineering & AI- Get Well Network Get Well Network - Bangalore Posted Apr 23, 2026

Title: DevOps Engineer

Reporting to: Senior Director, Product Development
Location: Bengaluru (Bangalore)

Opportunity:

Responsibilities:

Infrastructure Development & Integration

Design, implement, and manage cloud-native infrastructure (AWS, Azure, GCP) to support healthcare platforms, AI agents, and clinical applications.
Build and maintain scalable CI/CD pipelines to enable rapid and reliable delivery of software, data pipelines, and AI/ML models.
Design and manage Kubernetes (K8s) clusters for container orchestration, workload scaling, and high availability with integrated monitoring to ensure cluster health and performance
Implement Kubernetes-native tools (Helm, Kustomize, ArgoCD) for deployment automation and environment management ensuring observability through monitoring dashboards and alerts
Collaborate with Staff Engineers/Architects to align infrastructure with enterprise goals for scalability, reliability, and performance leveraging monitoring insights to inform architectural decisions.

System Optimization & Reliability

Implement and maintain comprehensive monitoring, logging, and alerting mechanisms (Prometheus, Grafana, ELK, Datadog, AWS cloudwatch, AWS cloud trail) to ensure real-time visibility into system performance, resource utilization, and potential incidents.
Implement monitoring, logging, and alerting mechanisms (Prometheus, Grafana, ELK, Datadog) to ensure system reliability and proactive incident response.
Ensure data pipeline workflows (ETL/ELT, real-time streaming, batch processing) are observable, reliable, and auditable.
Support observability and monitoring of GenAI pipelines, embeddings, vector databases, and agentic AI workflows.
Proactively analyze monitoring data to identify bottlenecks, predict failures, and drive continuous improvement in system reliability.

Compliance & Security

Support audit trails and compliance reporting through automated DevSecOps practices.
Implement security controls for LLM-based applications, AI agents, and healthcare data pipelines, including prompt injection prevention, API rate limiting, and data governance.

Collaboration & Agile Practices

Partner closely with software engineers, data engineers, AI/ML engineers, and product managers to deliver integrated, secure, and scalable solutions.
Contribute to agile development processes including sprint planning, stand-ups, and retrospectives.
Mentor junior engineers and share best practices in cloud-native infrastructure, CI/CD, Kubernetes, and automation.

Innovation & Technical Expertise

Stay informed about emerging DevOps practices, cloud-native architectures, MLOps/LLMOps, and data engineering tools.
Prototype and evaluate new frameworks and tools to enhance infrastructure for data pipelines, GenAI, and Agentic AI applications.
Advocate for best practices in infrastructure design, focusing on modularity, maintainability, and scalability.

Requirements

Education & Experience

Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical discipline.
6+ years of experience in DevOps, Site Reliability Engineering, or related roles, with at least 3+ years building cloud-native infrastructure.
Proven track record of managing production-grade Kubernetes clusters and cloud infrastructure in regulated environments.
Experience supporting GenAI/LLM applications (e.g., OpenAI, Hugging Face, LangChain) and vector databases (e.g., Pinecone, Weaviate, FAISS).
Hands-on experience supporting data pipeline products using ETL/ELT frameworks (Apache Airflow, dbt, Prefect) and streaming systems (Kafka, Spark, Flink).
Experience deploying AI agents and orchestrating agent workflows in production environments.

Technical Proficiency

Expertise in Kubernetes (K8s) for orchestration, scaling, and managing containerized applications.
Strong proficiency in containerization (Docker) and Kubernetes ecosystem tools (Helm, ArgoCD, Istio/Linkerd for service mesh).
Hands-on experience with Infrastructure as Code (Terraform, CloudFormation, or Pulumi).
Proficiency with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, ArgoCD, Spinnaker).
Familiarity with monitoring and observability tools (Prometheus, Grafana, ELK, Datadog, AWS cloud watch and AWS cloud trail), including setting up dashboards, alerts, and custom metrics for cloud-native and AI systems.
Good to have: knowledge of healthcare data standards (FHIR, HL7) and secure deployment practices for AI/ML and data pipelines.

Professional Skills

Strong problem-solving skills with a focus on reliability, scalability, and security.
Excellent collaboration and communication skills across cross-functional teams.
Proactive, detail-oriented, and committed to technical excellence in a fast-paced healthcare environment.

About Get Well:

Now part of the SAI Group family, Get Well is redefining digital patient engagement by putting patients in control of their personalized healthcare journeys, both inside and outside the hospital. Get Well is combining high-tech AI navigation with high-touch care experiences driving patient activation, loyalty, and outcomes while reducing the cost of care. For almost 25 years, Get Well has served more than 10 million patients per year across over 1,000 hospitals and clinical partner sites, working to use longitudinal data analytics to better serve patients and clinicians. AI innovator SAI Group led by Chairman Romesh Wadhwani is the lead growth investor in Get Well. Get Well’s award-winning solutions were recognized again in 2024 by KLAS Research and AVIA Marketplace. Learn more at Get Well and follow-us on LinkedIn and Twitter.

Get Well is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

About SAI Group:

SAIGroup commits to $1 Billion capital, an advanced AI platform that currently processes 300M+ patients, and 4000+ global employee base to solve enterprise AI and high priority healthcare problems. SAIGroup - Growing companies with advanced AI; https://www.cnbc.com/2023/12/08/75-year-old-tech-mogul-betting-1-billion-of-his-fortune-on-ai-future.html
Bio of our Chairman Dr. Romesh Wadhwani: Team - SAIGroup (Informal at Romesh Wadhwani - Wikipedia)
TIME Magazine recently recognized Chairman Romesh Wadhwani as one of the Top 100 AI leaders in the world - Romesh and Sunil Wadhwani: The 100 Most Influential People in AI 2023 | TIME

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Staff Data Engineer

Netradyne · Bangalore

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Analytics Bangalore Posted Apr 22, 2026

Netradyne harnesses the power of Computer Vision and Edge Computing to revolutionize the modern-day transportation ecosystem. We are a leader in fleet safety solutions. With growth exceeding 4x year over year, our solution is quickly being recognized as a significant disruptive technology. Our team is growing, and we need forward-thinking, uncompromising, competitive team members to continue to facilitate our growth.

About Netradyne:

Netradyne provides AI-powered technologies for fleet management and safer roads. An award-winning industry leader in fleet safety and video telematics solutions, Netradyne empowers thousands of commercial fleet customers across North America, Europe, and Asia to enhance their driver performance, reduce risk, and optimize operations.

Netradyne sets the standard among transportation technology companies for enhancing and sustaining road safety, with an industry-leading 25+ billion miles vision-analyzed for risk and an industry-first driver scoring system that reinforces safe behaviors. Founded in 2015, Netradyne is headquartered in San Diego with offices in San Francisco, Nashville, the UK and Bangalore. For more details visit: www.netradyne.com

Job Overview:

As a Staff Data Engineer – ML at Netradyne, an award-winning industry leader in fleet safety and video telematics solutions, you will take senior technical ownership of the machine learning and data platforms that underpin our AI-powered fleet analytics. This role is responsible for designing, building, and scaling production-grade ML pipelines, generative AI capabilities, and real-time data streaming systems across cloud and edge environments, delivering actionable insights that make fleet operations safer and more efficient. You will collaborate closely with machine learning engineers, data scientists, and product teams to integrate advanced AI technologies into Netradyne's platform, including on-device edge intelligence and natural-language-driven capabilities. Your work will directly shape the data infrastructure behind Netradyne's Physical AI vision, where AI continuously interprets multimodal vehicle data to understand drivers, vehicles, and road environments as an integrated system.

Key Responsibilities:

You will be embedded within a team of machine learning engineers and data scientists, responsible for building and productising generative AI, deep learning, and data engineering solutions. You will:
Design, develop and deploy production-ready, scalable solutions that utilise generative AI, traditional ML models, data science workflows, and ETL/ELT pipelines on AWS cloud infrastructure (and hybrid edge-cloud environments).
Build and manage real-time and batch data streaming pipelines to handle high-volume, high-velocity data from fleet devices, leveraging technologies such as Apache Kafka and Amazon Kinesis for low-latency processing and near real-time insights.
Collaborate with cross-functional teams (Product, Data Science, ML Engineering, Operations) to integrate AI-driven solutions into business operations and customer-facing products.
Design and implement generative AI solutions using large language models (LLMs), including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) patterns, to enable intelligent analytics, natural-language interfaces, and context-aware insights across fleet and safety data.
Build and scale agentic AI systems by developing autonomous and semi-autonomous agents that orchestrate data retrieval, reasoning, and actions across ML pipelines and services, ensuring these agentic workflows are production-grade, observable, and aligned with safety, reliability, and governance requirements.
Implement MLOps best practices including CI/CD pipelines for model training, automated testing, model versioning, continuous monitoring, and modern workflow orchestration (e.g. Apache Airflow, MLFlow) to achieve reliable, reproducible model deployments at scale.
Champion data quality and governance by implementing data contracts, rigorous validation, and monitoring to ensure that analytical pipelines meet defined SLAs and that downstream models and business users can trust the data.
Conduct research and stay current with the latest advancements in generative AI, vector search techniques, LLM frameworks, orchestration platforms, and related technologies.

Mandatory Skills:

Experience with data visualisation and BI tools (e.g. Tableau, Grafana, Plotly Dash).
Exposure to real-time data streaming and messaging systems (e.g. Apache Kafka, Amazon Kinesis, Amazon SQS).
Knowledge of containerisation and orchestration (e.g. Docker, Kubernetes/EKS)
Strong understanding of generative AI system design, including prompt engineering, RAG architectures, vector search, and evaluation techniques for LLM-based applications in production environments.
Experience with agentic AI patterns, such as designing, orchestrating, and monitoring autonomous or semi-autonomous agents that coordinate tools, data sources, and ML services with appropriate safety, observability, and governance controls.
Experience with modern workflow orchestration platforms such as Apache Airflow, Prefect, or Dagster for scheduling and managing complex ETL/ML pipelines. These tools are now standard for data pipeline engineering.
Proficiency with at least one Python web framework (e.g. FastAPI, Django, Flask) for developing data or model-serving APIs.
Experience with rapid prototyping tools (e.g. Streamlit, Gradio, Dash) for demonstrating ML solutions to stakeholders.
Familiarity with modern ML frameworks and libraries such as PyTorch, TensorFlow, and Hugging Face Transformers
Background in large-scale data processing and lakehouse or data warehousing technologies (e.g. Snowflake, Amazon Redshift, Apache Spark/EMR, Delta Lake).

Qualifications and Education Requirements:

B.Tech, M.Tech or PhD in Computer Science, Data Science, Electrical Engineering, Statistics, Mathematics, Operations Research, or a related field (or equivalent professional experience).
5–8 years of industry experience in data engineering, machine learning engineering, or related roles, with a track record of building and scaling data/ML solutions in production.
Strong programming skills in Python and SQL, with solid fundamentals in algorithms, data structures, and object-oriented programming.
Experience building end-to-end solutions on AWS cloud infrastructure including developing data pipelines (ETL/ELT), deploying ML models at scale, and utilising cloud services (e.g. S3, Lambda, EKS).
In-depth understanding of data storage systems: proficient with relational databases (SQL), NoSQL datastores, and modern vector databases, including schema design and query optimisation for large-scale datasets.
Hands-on experience with generative AI tools and workflows, and practical work with large language models (LLMs), including building LLM-powered applications and utilising RAG techniques to incorporate external knowledge.
Working knowledge of MLOps principles and tools — e.g. model lifecycle management, CI/CD pipelines for ML, automated data/feature pipelines, and monitoring/alerting for deployed models.
Strong analytical and problem-solving skills with keen attention to detail.
Solid foundation in statistics, probability, and estimation theory.

Equal Opportunity Employer Statement:
Netradyne is an equal opportunity employer and are committed to creating an inclusive environment for all employees.

We are committed to an inclusive and diverse team. Netradyne is an equal-opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status.

If there is a match between your experiences/skills and the Company's needs, we will contact you directly.

Netradyne is an equal-opportunity employer.

Applicants only - Recruiting agencies do not contact.

Recruitment Fraud Alert!

There has been an increase in fraud that targets job seekers. Scammers may present themselves to job seekers as Netradyne employees or recruiters. Please be aware that Netradyne does not request sensitive personal data from applicants via text/instant message or any unsecured method; does not promise any advance payment for work equipment set-up and does not use recruitment or job-sourcing agencies that charge candidates an advance fee of any kind. Official communication about your application will only come from emails ending in ‘@netradyne.com’ or ‘@us-greenhouse-mail.io’.

Please review and apply to our available job openings at Netradyne.com/company/careers. For more information on avoiding and reporting scams, please visit the Federal Trade Commission's job scams website.

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Principal Data Software Engineer

Get Well Network · Bengaluru, Karnataka, India

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Engineering & AI- Get Well Network Get Well Network - Bangalore Posted Apr 18, 2026

Title: Principal Data Software Engineer

Location: Bengaluru (Bangalore)

Opportunity:

Get Well is seeking a visionary and technically adept Principal Data Software Engineer to design, develop and optimize our cloud-native data platform supporting AI, analytics, and clinical applications. This role is pivotal in architecting scalable, secure, and high-performance data processing systems within a regulated healthcare environment.

The ideal candidate brings deep technical expertise in data engineering, data governance, cloud infrastructure and hands-on experience with healthcare data standards, EMR integration, and clinical ontologie. The candidate should have a proven record of building secure, scalable data platforms. This position reports to the Senior Director, Product Development. This role requires close collaboration with data engineers, product teams, AI engineers and compliance specialists to deliver accurate, accessible, and actionable data solutions.

Responsibilities:

Platform Architecture & Design

Design and implement scalable, secure, and efficient data architectures (e.g., data lakehouse, medallion architecture) to support enterprise AI and analytics initiatives.
Define technical specifications for data ingestion, transformation, storage, and access layers.
Evaluate and recommend tools, frameworks, and cloud infrastructure to optimize performance, scalability, and cost-efficiency.
Ensure architectural alignment with organizational AI, analytics, and clinical application goals.

Data Engineering & Operations

Develop and maintain high-performance data pipelines for both batch and streaming data processing, leveraging tools such as Apache Spark, Databricks or Snowflake.
Implement deployment and orchestration frameworks (e.g., Airflow, dbt, Spark, Databricks, Snowflake)
Adhere to engineering best practices for CI/CD, observability, incident response, and SLA adherence
Optimize data processing systems for performance, reliability, and reusability.

Mentor engineers to foster technical growth and ensure alignment with best practices in data engineering.

Governance, Quality & Compliance

Collaborate with data governance and compliance teams to implement data security, encryption, and access control policies in line with HIPAA, GDPR, and other regulations.
Ensure data quality through validation, lineage tracking, and metadata management practices.
Support the development and maintenance of data catalogs for discoverability and stewardship

Collaboration & Technical Leadership

Partner with data engineers, product teams, and clinical informatics specialists to deliver integrated data solutions.
Provide technical guidance and mentorship to junior engineers, fostering a culture of technical excellence and collaboration.
Communicate complex technical designs and solutions to both technical and non-technical stakeholders effectively.
Contribute to agile development practices, participating in code reviews, design discussions, and continuous improvement initiatives.

Innovation & Technical Expertise

Stay informed about emerging trends in data engineering, cloud-native architectures, and healthcare data standards.
Prototype and evaluate modern data frameworks and tools (e.g., Delta Lake, Apache Iceberg) to enhance platform capabilities.
Communicate complex technical concepts to both technical and non-technical stakeholders.
Advocate for best practices in data platform design to ensure scalability, explainability, and compliance in AI-driven systems.

Requirements:

Education & Experience

Bachelor’s or Master’s degree in Computer Science or related technical discipline
12+ years of experience with at least 4+ years in data engineering or platform roles
Proven track record of designing and implementing cloud-native data processing systems.

Technical Proficiency

Advanced proficiency in Python, Scala, SQL, and distributed data processing frameworks such as Apache Spark.
Hands-on experience with cloud-based data platforms (e.g., Databricks, Snowflake, BigQuery, or Redshift).
Demonstrated ability to transform raw clinical data into curated, ML-ready datasets for analytics and AI applications.
Hands-on expertise in healthcare data standards including FHIR, HL7, USCDI, and CCDA

Professional Skills

Strong problem-solving skills with a focus on delivering scalable and maintainable solutions.
Excellent collaboration and communication skills, with the ability to work effectively in cross-functional teams.
Proactive, detail-oriented, and committed to driving technical excellence in a fast-paced environment.

About Get Well:

Now part of the SAI Group family, Get Well is redefining digital patient engagement by putting patients in control of their personalized healthcare journeys, both inside and outside the hospital. Get Well is combining high-tech AI navigation with high-touch care experiences driving patient activation, loyalty, and outcomes while reducing the cost of care. For almost 25 years, Get Well has served more than 10 million patients per year across over 1,000 hospitals and clinical partner sites, working to use longitudinal data analytics to better serve patients and clinicians. AI innovator SAI Group led by Chairman Romesh Wadhwani is the lead growth investor in Get Well. Get Well’s award-winning solutions were recognized again in 2024 by KLAS Research and AVIA Marketplace. Learn more at Get Well and follow-us on LinkedIn and Twitter.

Get Well is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

About SAI Group:

SAIGroup commits to $1 Billion capital, an advanced AI platform that currently processes 300M+ patients, and 4000+ global employee base to solve enterprise AI and high priority healthcare problems. SAIGroup - Growing companies with advanced AI; https://www.cnbc.com/2023/12/08/75-year-old-tech-mogul-betting-1-billion-of-his-fortune-on-ai-future.html
Bio of our Chairman Dr. Romesh Wadhwani: Team - SAIGroup (Informal at Romesh Wadhwani - Wikipedia)
TIME Magazine recently recognized Chairman Romesh Wadhwani as one of the Top 100 AI leaders in the world - Romesh and Sunil Wadhwani: The 100 Most Influential People in AI 2023 | TIME

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Data Software Engineer

Get Well Network · Bangalore

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Engineering & AI- Get Well Network Get Well Network - Bangalore Posted Apr 15, 2026

Opportunity

Get Well is seeking a skilled and motivated Software Data Engineer to help implement and scale our cloud-native data platform supporting AI, analytics, and clinical applications. This role involves building, testing, and optimizing secure and high-performance pipelines and workflows that power critical healthcare applications.

As a Software Data Engineer, you will collaborate closely with staff and senior engineers to deliver robust data infrastructure in a regulated, compliance-driven healthcare environment. You’ll gain deep exposure to modern tools and cloud technologies while contributing meaningfully to transforming healthcare delivery through data and AI.

Responsibilities

Data Engineering & Pipeline Development

Implement and maintain reliable batch and real-time data pipelines using modern frameworks such as Apache Spark, Databricks, and Snowflake.
Support ingestion, transformation, and delivery of structured and semi-structured data across cloud-native platforms.
Contribute to performance tuning and optimization efforts to ensure scalable and cost-effective workflows.
Utilize orchestration tools like Airflow, Temporal and dbt to enable automation, scheduling, monitoring, and version control of pipeline operations.

Data Quality & Compliance

Enforce data quality through the implementation of validation checks, data lineage tracking, and schema enforcement.
Assist in meeting healthcare compliance standards (e.g., HIPAA, GDPR) by implementing best practices for data handling, encryption, and access controls.
Work with metadata and data cataloging systems to ensure accuracy, transparency, and discoverability of enterprise datasets.

Technical Implementation & Collaboration

Participate in agile development practices, including daily stand-ups, sprint planning, retrospectives, and backlog grooming.
Support code reviews and debugging efforts to uphold code reliability, reusability, and maintainability.
Collaborate with cross-functional teams, including Data Science, Product, Quality, and Security, to deliver coordination and alignment on technical implementations.

Learning & Growth

Stay current on evolving technologies in cloud data engineering, including tools such as Delta Lake, Iceberg, and healthcare interoperability standards.
Actively engage in knowledge sharing and continuous learning through team discussions, peer programming, and internal demos.
Show initiative in exploring process improvements, automation opportunities, and platform enhancements.

Qualifications

Education & Experience

Bachelor’s degree in Computer Science, Engineering, or related field.
2–5 years of hands-on experience in data engineering, platform development, or software engineering focused on data systems.
Software development experience at a healthcare company (provider space preferred), with exposure to EHR systems or healthcare data domains is strongly preferred.

Technical Skills

Proficiency in Python and SQL for building and maintaining data workflows.
Experience working with distributed data frameworks like Apache Spark or Databricks.
Familiarity with data orchestration tools such as Airflow, Temporal and data modeling tools like dbt.
Experience with data platforms such as Azure data factory, databricks, etc.
Exposure to cloud providers - Azure preferred.
Exposure to healthcare data types (e.g., FHIR, HL7, CCDA) and terminologies (e.g., ICD, SNOMED) is a strong plus.

Professional Attributes

Strong analytical and problem-solving skills with attention to performance and reliability.
Effective communicator and team player who thrives in collaborative, cross-functional settings.
Eagerness to learn new tools and technologies and contribute to platform evolution in a fast-paced environment.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

Ready to apply?

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Staff Solutions Engineer

JazzX AI · Bangalore, Karnataka

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Sales - JazzX JazzX- Bangalore Posted Apr 15, 2026

About JazzX AI:

Vision: Enterprises operating on institutional intelligence—governed, self-improving, and scalable beyond individual expertise.

JazzX AI is defining the future of enterprise work—by building AI-native digital workers that actually get the job done.

We believe enterprises don't scale expertise—they lose it. Knowledge stays trapped in individuals, judgment gets applied inconsistently, and the best talent spends time on work that should run itself. We're changing that.

JazzX AI transforms messy enterprise reality into institutional intelligence: governed digital workers that capture expert judgment, make every decision explainable, and continuously improve through real-world execution. The result is faster decisions, higher-quality outcomes, and reliable execution at scale—in domains where getting it wrong isn't an option.

We're starting with lending and due-diligence workflows—complex, regulated, high-stakes. From here, we're building the backbone for enterprise intelligence across industries.

This is early-stage, hard, and consequential work. If you want to be part of bringing AI systems to market that actually run in production, handle real complexity, and deliver real outcomes—not demos, not chatbots—JazzX AI is the place.

Headquartered in Los Altos, CA. Backed by SAIGroup.

About SAIGroup :

SAIGroup a private investment firm that has committed $1B to build and scale next-generation, AI-powered enterprise software companies. SAIGroup’s portfolio serves 2,000+ global enterprise customers, generates nearly $800M in annual revenue, and employs 4,000+ people worldwide — providing JazzX AI with long-term capital, deep operating expertise, and access to real-world enterprise scale from day one.

Learn more about JazzX AI:
Website: https://jazzx.ai
LinkedIn: https://www.linkedin.com/company/jazzx-ai

Learn more about SAIGroup:
Website: https://saigroup.ai

Role Overview

As a Staff Solutions Engineer, you will play a strategic, hands-on role in transforming JazzX’s AGI platform into scalable, high-impact solutions for enterprise customers. With your deep technical expertise and leadership, you’ll drive the design, development, and deployment of LLM-powered applications across complex client environments.

You will:

Lead the integration of LLM features, vector search pipelines, and agentic workflows into production systems.
Partner with solution architects, product managers, and customer success teams across the full solution lifecycle—from discovery through deployment and optimization.
Influence core platform enhancements by contributing real-world learnings and reusable components.
Set the technical bar through design leadership, mentoring, and rigorous engineering practices.

Key Responsibilities

Solution Architecture & Implementation

Architect and implement end-to-end AGI solutions, including retrieval-augmented generation (RAG), tool-using agents, and LLM orchestration patterns.
Design and integrate secure data pipelines, APIs, and authorization layers tailored to customer environments.
Make high-impact, component-level design decisions, balancing performance, maintainability, and customer goals.

Delivery Leadership

Own delivery of proof-of-concepts, pilots, and scalable production rollouts in agile settings.
Ensure production readiness through observability (logs, metrics, tracing) and contribute to incident response/on-call rotations as needed.

Collaboration & Enablement

Work closely with research and product teams to test and validate emerging LLM techniques in customer contexts.
Serve as a technical escalation point for customer implementations, proactively identifying and resolving complex issues.
Mentor junior engineers and contribute to internal best practices through code reviews, demos, and documentation.

Innovation & Thought Leadership

Evaluate and pilot emerging frameworks (e.g., AutoGen, LangGraph, WASM inference engines) and contribute reusable assets to the internal platform.
Shape JazzX’s field engineering playbook by sharing insights, reusable templates, and domain-specific solutions.

Qualifications

Must-Have

8+ years of experience in professional software engineering, with at least 3+ years working on ML, data, or AI/LLM-centric systems.
Strong expertise in Python (or Go/Java), with production-grade coding, testing, and CI/CD best practices.
Proficiency in modern GenAI/LLM frameworks (e.g., LangChain, LlamaIndex, HuggingFace Transformers, PyTorch, TensorFlow) and vector databases (e.g., Pinecone, Weaviate, FAISS).
Familiarity with integrating REST/GraphQL APIs, Kafka streams, and relational/non-relational databases.
Excellent communication skills and the ability to work cross-functionally with engineering, product, and customer stakeholders.
Willingness to travel up to 20% for key customer engagements.

Nice-to-Have

Experience delivering RAG, fine-tuning, or agentic solutions in regulated industries (e.g., finance, healthcare, telecom).
Any Certifications in cloud
Exposure to MLOps and data engineering tools (e.g., MLflow, Kubeflow, Vertex AI, Airflow, dbt).

Attributes We Value

Technical Leadership – You take ownership, guide architecture decisions, and raise the bar for engineering quality.
Customer Focus – You thrive on solving real-world challenges and building trust with technical stakeholders.
Startup Mindset – You move fast, embrace ambiguity, and iterate quickly.
Collaboration & Mentorship – You elevate those around you through thoughtful feedback, knowledge sharing, and support.
Mission-Driven – You’re motivated by the opportunity to shape the future of intelligent, human-centric software.

Why Join JazzX AI:

What draws people to JazzX AI is the opportunity to build something truly foundational.

We are at the beginning of a new era — one where enterprise systems will no longer be static tools, but dynamic collaborators that learn, reason, and evolve alongside the people who use them. At JazzX AI, you’ll help build a platform that redefines how work happens in the AGI era.

JazzX AI brings together vision, deep technology, and purpose. This is not about experimenting with AI features; it’s about turning the promise of AGI into practical, auditable, and human-aligned systems that enterprises can trust and rely on at scale. The work here directly impacts productivity, efficiency, and decision-making in complex, real-world environments.

If you’re motivated by building systems that matter — systems that combine intelligence with responsibility — JazzX AI offers the chance to do that work at a deeper level, with real ownership and lasting impact.

Ready to apply?

Apply to JazzX AI

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JazzX AI

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JA

Staff / Senior AGI Solutions Engineer

JazzX AI · Bangalore, Karnataka

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Sales - JazzX JazzX- Bangalore Posted Apr 15, 2026

About JazzX AI:

Vision: Enterprises operating on institutional intelligence—governed, self-improving, and scalable beyond individual expertise.

JazzX AI is defining the future of enterprise work—by building AI-native digital workers that actually get the job done.

We believe enterprises don't scale expertise—they lose it. Knowledge stays trapped in individuals, judgment gets applied inconsistently, and the best talent spends time on work that should run itself. We're changing that.

JazzX AI transforms messy enterprise reality into institutional intelligence: governed digital workers that capture expert judgment, make every decision explainable, and continuously improve through real-world execution. The result is faster decisions, higher-quality outcomes, and reliable execution at scale—in domains where getting it wrong isn't an option.

We're starting with lending and due-diligence workflows—complex, regulated, high-stakes. From here, we're building the backbone for enterprise intelligence across industries.

This is early-stage, hard, and consequential work. If you want to be part of bringing AI systems to market that actually run in production, handle real complexity, and deliver real outcomes—not demos, not chatbots—JazzX AI is the place.

Headquartered in Los Altos, CA. Backed by SAIGroup.

About SAIGroup :

SAIGroup a private investment firm that has committed $1B to build and scale next-generation, AI-powered enterprise software companies. SAIGroup’s portfolio serves 2,000+ global enterprise customers, generates nearly $800M in annual revenue, and employs 4,000+ people worldwide — providing JazzX AI with long-term capital, deep operating expertise, and access to real-world enterprise scale from day one.

Learn more about JazzX AI:
Website: https://jazzx.ai
LinkedIn: https://www.linkedin.com/company/jazzx-ai

Learn more about SAIGroup:
Website: https://saigroup.ai

Job Title: Senior AGI Engineer – GTM Solution Delivery

Role Overview

As a Senior AGI Engineer you are the hands-on technical force that turns JazzX’s AGI platform into working, measurable solutions for customers. You will:

Build and integrate LLM-driven features, vector search pipelines, and tool-calling agents into client environments.

Collaborate with solution architects, product, and customer-success teams from discovery through production rollout.

Contribute field learnings back to the core platform, accelerating time-to-value across all deployments.

You are as comfortable writing production-quality Python as you are debugging Helm charts, and you enjoy explaining your design decisions to both peers and client engineers.

Key Responsibilities

Focus Area	What You’ll Do
Solution Implementation	* Develop and extend JazzX AGI services (LLM orchestration, retrieval-augmented generation, agents) within customer stacks. * Integrate data sources, APIs, and auth controls; ensure solutions meet security and compliance requirements. * Pair with Solution Architects on design reviews; own component-level decisions.
Delivery Lifecycle	* Drive proofs-of-concept, pilots, and production rollouts with an agile, test-driven mindset. * Create reusable deployment scripts (Terraform, Helm, CI/CD) and operational runbooks. * Instrument services for observability (tracing, logging, metrics) and participate in on-call rotations.
Collaboration & Support	* Work closely with product and research teams to validate new LLM techniques in real-world workloads. * Troubleshoot customer issues, triage bugs, and deliver patches or performance optimisations. * Share best practices through code reviews, internal demos, and technical workshops.
Innovation & Continuous Learning	* Evaluate emerging frameworks (e.g., LlamaIndex, AutoGen, WASM inferencing) and pilot promising tools. * Contribute to internal knowledge bases and GitHub templates that speed future projects.

Qualifications

Must-Have

5+ years of professional software engineering experience; 2+ years working with ML or data-intensive systems.

Proficiency in Python (or Java/Go) with strong software-engineering fundamentals (testing, code reviews, CI/CD).

Hands-on experience deploying containerised services on AWS, GCP, or Azure using Kubernetes & Helm.

Practical knowledge of LLM / Gen-AI frameworks (LangChain, LlamaIndex, PyTorch, or TensorFlow) and vector databases.

Familiarity integrating REST/GraphQL APIs, streaming platforms (Kafka), and SQL/NoSQL stores.

Clear written and verbal communication skills; ability to collaborate with distributed teams.

Willingness to travel 10–20 % for key customer engagements.

Nice-to-Have

Experience delivering RAG or agent-based AI solutions in regulated domains (finance, healthcare, telecom).

Cloud or Kubernetes certifications (AWS SA-Assoc/Pro, CKA, CKAD).

Exposure to MLOps stacks (Kubeflow, MLflow, Vertex AI) or data-engineering tooling (Airflow, dbt).

Attributes

Empathy & Ownership: You listen carefully to user needs and take full ownership of delivering great experiences.

Startup Mentality: You move fast, learn quickly, and are comfortable wearing many hats.

Detail-Oriented: You care about the little things

Mission-Driven: You want to solve important, high-impact problems that matter to real people.

Team-Oriented: Low ego, collaborative, and excited to build alongside highly capable engineers, designers, and domain experts.

Travel

This position requires the ability to travel to client sites as needed for on-site deployments and collaboration. Travel is estimated at approximately 20–30% of the time (varying by project), and flexibility is expected to accommodate key client engagement activities.

Why Join JazzX AI:

What draws people to JazzX AI is the opportunity to build something truly foundational.

We are at the beginning of a new era — one where enterprise systems will no longer be static tools, but dynamic collaborators that learn, reason, and evolve alongside the people who use them. At JazzX AI, you’ll help build a platform that redefines how work happens in the AGI era.

JazzX AI brings together vision, deep technology, and purpose. This is not about experimenting with AI features; it’s about turning the promise of AGI into practical, auditable, and human-aligned systems that enterprises can trust and rely on at scale. The work here directly impacts productivity, efficiency, and decision-making in complex, real-world environments.

If you’re motivated by building systems that matter — systems that combine intelligence with responsibility — JazzX AI offers the chance to do that work at a deeper level, with real ownership and lasting impact.

Ready to apply?

Apply to JazzX AI

JA

JazzX AI

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GE

Senior Data Software Engineer

Get Well Network · Bangalore

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Engineering & AI- Get Well Network Get Well Network - Bangalore Posted Apr 15, 2026

Opportunity

Get Well is hiring a highly motivated Senior Data Software Engineer to help build and scale our modern cloud-native data platform that supports AI, analytics, and clinical applications. You'll focus on developing robust and compliant data processing workflows while working closely with platform and architecture teams to operationalize next-generation, healthcare-specific data systems.

This role is ideal for an experienced engineer passionate about transforming complex healthcare data into meaningful applications through engineering excellence, collaboration, and innovation. You will play a key role in the continued growth of our data platform and help ensure that our data systems are secure, reliable, and high-performing within the healthcare industry.

Candidates must have hands-on software development experience with at least one healthcare company—preferably in the provider space—with exposure to EHRs and core healthcare data domains.

Responsibilities

Data Engineering & Pipeline Development

Design, implement, and maintain scalable batch and real-time data pipelines across a variety of sources and formats.
Develop high-performance ETL/ELT workflows using tools and frameworks such as Apache Spark, Databricks, dbt, and Snowflake.
Collaborate with Staff Engineers and Architects to translate platform architecture into executable, maintainable solutions.
Automate data orchestrations using Airflow or other workflow managers to enable continuous data processing and delivery.

Healthcare Data Integration & Compliance

Ingest and normalize healthcare datasets (e.g., EHR, FHIR, HL7, CCDA, Claims) in accordance with internal data models.
Work with governance and compliance teams to meet regulatory requirements including HIPAA and GDPR.
Implement best practices for encryption, data masking, access control, and auditability across the platform.
Support efforts around metadata management, data lineage, and structured logging for traceability and transparency.

Platform Optimization & Technical Execution

Tune Spark-based pipelines and SQL transformations for performance, reliability, and resource efficiency.
Participate in code reviews, unit testing, and CI/CD processes to ensure code quality and maintainability.
Work collaboratively across product, informatics, and DevOps teams to translate business needs into technical solutions.
Contribute to documentation, analytics enablement, and reusability of shared platform components.

Growth, Mentorship & Best Practices

Mentor junior engineers through code reviews, paired programming, and collaborative development practices.
Model and advocate for engineering best practices, including clean architecture, effective testing, and proactive monitoring.
Stay current with trends in distributed systems, cloud-native computing, data privacy, and healthcare interoperability.
Propose and implement technical upgrades and innovative approaches based on tools like Delta Lake, Apache Iceberg, and emerging GenAI capabilities.

Qualifications

Education & Experience

Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field.
6+ years of relevant experience in data engineering roles, with at least 3 years focused on cloud-native or large-scale data systems.
Must have software development experience in at least one healthcare company, preferably in the provider space, with exposure to EHR systems or key healthcare data domains.
Direct experience designing and building pipelines that move and transform healthcare data, with production-quality data quality checks at scale.

Technical Skills

Proficient in Python, SQL, and Apache Spark for distributed processing and transformation.
Hands-on experience with modern data platforms—such as Snowflake, Databricks, Redshift, or BigQuery.
Deep experience working with public cloud providers, particularly Azure, including native services for data storage, processing, and orchestration (e.g., Azure Data Lake, Azure Synapse).
Experience with orchestration tools like Airflow and transformation layers such as dbt.
Familiar with data pipelines in regulated environments, including auditing, encryption, and compliance controls.
amiliarity with healthcare-specific data formats (FHIR, HL7, EDI) and terminologies (ICD-10, SNOMED, LOINC).

Professional Attributes

Strong problem-solving skills with a focus on quality, performance, and pragmatism.
Excellent communication and teamwork skills, with the ability to work across multidisciplinary teams.
High accountability and ownership mindset with a commitment to excellence in healthcare technology.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

Ready to apply?

GE

Get Well Network

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Senior Data Engineer, Payments

Airbnb · Bangalore, India

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Software Engineering Bangalore, India Posted Apr 13, 2026

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join:

The Payments team at Airbnb is crucial to the company's operations, handling critical data related to compliance with Tax, Payments, and Legal regulations. We also manage application data for tools such as CRM, Jira, and Workday, which are essential for Airbnb’s business. Joining this team means working with cross-functional stakeholders, designing scalable solutions, and contributing to a world-class data engineering environment with an emphasis on quality, scalability, and robust engineering practices.

The Difference You Will Make:

Our team charter is on enabling Airbnb to comply with Tax, Payments,and Legal regulations so that our Hosts can continue to operate in regulated geos. Our products ingest, process, validate, and deliver large datasets to government authorities (often partnered with tax remittance) so our data must be of the highest accuracy and quality. As you build and maintain key components of the critical Compliance data ecosystem, you’ll have the opportunity to contribute to creating standards and best practices for Airbnb’s DataEngineering. Your work on solving complex business challenges at scale will be instrumental in shaping the tools, processes, and standards used by the broader data community.

A Typical Day:

Design, build, and maintain robust and efficient data pipelines that collect, process, and store data from various sources, including user interactions, listing details, and external data feeds.
Develop data models that enable the efficient analysis and manipulation of data for merchandising optimization. Ensure data quality, consistency, and accuracy.
Develop high quality data assets for product use-cases by partnering with Product, AI/ML and Data Science.
Build scalable data pipelines (SparkSQL & Scala) leveraging Airflow scheduler/executor framework
Collaborate with cross-functional teams, including Data Scientists, Product Managers, and Software Engineers, to define data requirements, and deliver data solutions that drive merchandising and sales improvements.
Contribute to the broader Data Engineering community at Airbnb to influence tooling and standards to improve culture and productivity
Improve code and data quality by leveraging and contributing to internal tools to automatically detect and mitigate issues

Your Expertise:

6+ years of relevant industry experience
BE/B.tech in computer science or relevant technical degree
Hands on experience in DSA coding -Data structure and algorithm
Extensive experience designing, building, and operating robust distributed data platforms (e.g., Spark, Kafka, Flink, HBase) and handling data at the petabyte scale.
Strong knowledge of Scala, or Python, and expertise with data processing technologies and query authoring (SQL).
Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions
Expertise with ETL schedulers such as Apache Airflow, Luigi, Oozie, AWS Glue or similar frameworks
Solid understanding of data warehousing concepts and hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)
Excellent written and verbal communication skills

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

Ready to apply?

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Airbnb

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Senior Data Scientist - Ad Optimization, India

Branch Metrics · Bengaluru, Karnataka, India

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310 Engineering Bangalore Posted Apr 8, 2026

At Branch, we power every touchpoint with links that work and insights that prove it. From click to conversion, we make growth measurable. Our unparalleled attribution, backed by AI-enhanced linking, is trusted to deliver seamless experiences that increase ROI, decrease wasted spend, and eliminate siloed attribution.

We bring the same rigor to how we build our team, by empowering our people to move fast, own outcomes, and build something that matters. We take pride in making meaningful investments in our team’s health, wealth, and growth so individuals can thrive as we scale. Our culture values smart, humble, and collaborative teammates who take accountability and drive results in an environment where their work truly moves the business forward.

We are innovative, scaling with purpose, and led by seasoned leaders who know how to build enduring companies. Trusted by brands like Instacart, Western Union, NBCUniversal, ZocDoc, and Sephora, we’re big enough to matter, small enough for you to make a real impact. If you’re excited by the grit of building, rapid learning, and shaping the future of customer growth, you’ll find your place here.

We are seeking an experienced and highly skilled Senior Data Scientist to lead our efforts in optimizing ad display on native Android surfaces. In this role, you will design and implement data-driven strategies to maximize ad effectiveness, user engagement, and revenue. You will collaborate closely with product managers, engineers, and cross-functional teams to drive innovation, improve ad relevance, and ensure a seamless user experience.

As a Senior Data Scientist, you’ll get to:

Develop and refine data-driven ad optimization strategies tailored to native Android environments, focusing on user engagement, personalization, and revenue uplift.
Design, implement, and improve predictive models for ad targeting, recommendation, and bidding strategies using cutting-edge machine learning and statistical techniques.
Lead the design and analysis of experiments to test ad placements, formats, and targeting methods. Use data from A/B tests and multivariate testing to validate hypotheses and inform decisions.
Analyze user behavior patterns to understand engagement and dropout points, leveraging insights to optimize ad positioning, timing, and relevance.
Partner with product managers, engineers, designers, and marketing teams to align ad strategies with business objectives and user experience goals. Communicate insights and recommendations effectively to both technical and non-technical stakeholders.
Ensure the scalability of ad models across a wide range of Android devices and varying network conditions. Work closely with engineering teams to deploy and monitor models in a production environment.
Provide mentorship and guidance to junior data scientists, fostering a collaborative and innovative team environment. Lead by example in developing high-quality, scalable solutions for complex ad optimization challenges.

You’ll be a good fit if you have:

PhD (preferred) or Master's Degree (required) in Computer Science, Data Science, Statistics, Machine Learning, or a related field.
6+ years of experience in data science or machine learning, with a strong focus on ad technology or user experience optimization.
Demonstrable experience in working with ad serving, ad tech stacks, and optimization techniques, especially within Android or mobile ecosystems.
Expertise in machine learning frameworks (TensorFlow, PyTorch, or similar).
Advanced proficiency in Python, or Kotlin.
Experience with data processing and pipeline tools (e.g., Spark, Hadoop, Airflow).
Deep understanding of A/B testing, causal inference, and other experimentation methods.
Familiarity with ad tech, programmatic advertising, and user behavior metrics, particularly in the context of mobile and Android platforms.
Excellent analytical, problem-solving, and communication skills. Proven ability to articulate complex data science concepts to stakeholders across different domains.

Nice to have:

Previous experience optimizing ad displays on native mobile or Android surfaces.
Familiarity with the Android SDK and understanding of native Android UI/UX design principles.
Knowledge of reinforcement learning, multi-armed bandit models, and contextual targeting techniques.

This role is based at our Bengaluru, India office and follows a Hybrid schedule that will be aligned with our Return to Office guidelines.

The salary range provided represents base compensation and does not include potential equity, which is available for qualifying positions. At Branch, we are committed to the well-being of our team by offering a comprehensive benefits package. From health and wellness programs to paid time off and retirement planning options, we provide a range of benefits for qualified employees. For detailed information on the benefits specific to your position, please consult with your recruiter.

Branch is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

If you think you'd be a good fit for this role, we'd love for you to apply! At Branch, we strive to create an inclusive culture that encourages people from all walks of life to bring their unique, diverse perspectives to work. We aim every day to build an environment that empowers us all to do the best work of our careers, and we can't wait to show you what we have to offer!

A little bit about us:

Branch is the leading provider of engagement and performance mobile SaaS solutions for growth-focused teams, trusted to maximize the value of their evolving digital strategies. The Branch platform provides a seamless experience across paid and organic, on all channels and platforms, online and offline, to eliminate friction and drive valuable action at the moments of highest intent. With Branch, businesses gain accurate mobile measurement and insights into user interactions, enabling them to drive conversions, engagement, and more intelligent marketing spend.

Branch is an award-winning employer headquartered in Mountain View, CA. World-class brands like Instacart, Western Union, NBCUniversal, Zocdoc and Sephora acquire users, retain customers and drive more conversions with Branch.

Candidate Privacy Information:
For more information on the data that Branch will collect through your application, and how we use, share, delete, and retain that information as part of our recruitment and employment efforts, please see our HR Privacy Policy.

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Apply to Branch Metrics

Branch Metrics

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Senior Machine Learning Engineer

Tekion · Bengaluru, Karnataka, India

Apply now

Engineering Bangalore HQ Posted Apr 7, 2026

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

Build and operate the production backbone that takes models from Applied Sciences (AS) and delivers reliable, low-latency ML services across Tekion’s DMS, CRM, Digital Retail, Service, Payments, and enterprise products. You’ll own pipelines, microservices, CI/CD, observability, and runtime reliability—working hand-in-hand with Applied Sciences and Product to turn ideas into measurable dealer and consumer impact.

Why this Role Matters

Accelerate the rollout of LLM-powered and agent-driven features across Tekion products.

Enable agentic workflows that automate, reason, and interact on behalf of users and internal stakeholders.

Operationalize secure, compliant, and explainable LLM and agentic services at scale.

Convert Applied Sciences models into scalable, compliant, cost‑efficient production services.

Standardize how models are trained, validated, deployed, and monitored across Tekion products.

Power real-time, context-aware experiences by integrating batch/stream features, graph context, and online inference.

What You’ll Do

Turn Applied Sciences prototype models (tabular, NLP/LLM, recommendation, forecasting) into fast, reliable services with well-defined API contracts.

Integrate with the LLM Gateway/MCP, prompt/config versioning.

Build and orchestrate CI/CD pipelines.

Review data science models; refactor and optimize code; containerize; deploy; version; and monitor for quality.

Collaborate with data scientists, data engineers, product managers, and architects to design enterprise systems.

Monitor, detect, and mitigate risks unique to LLMs and agentic systems.

Implement prompt management: versioning, A/B testing, guardrails, and dynamic orchestration based on feedback and metrics.

Design batch/stream pipelines (Airflow/Kubeflow, Spark/Flink, Kafka) and online features linked to our domain graph.

Build inference microservices (REST/gRPC) with schema versioning, structured outputs, and stringent p95 latency targets.

Manage the model/feature lifecycle: feature store strategy, model/agent registry, versioning, and lineage.

Instrument deep observability: traces/logs/metrics, data/feature drift, model performance, safety signals, and cost tracking.

Ensure real-time reliability: autoscaling, caching, circuit breakers, retries/fallbacks, and graceful degradation.

Develop templates/SDKs/CLIs, sandbox datasets, and documentation that make shipping ML the default path.

Desired Skills and Experience

6+ years in ML engineering/MLOps or backend/platform engineering with production ML.

Experience with LLMs, retrieval systems, vector stores, and graph/knowledge stores.

Strong software engineering fundamentals: Python plus one of Java/Go/Scala; API design; concurrency; testing.

Hands-on with orchestration frameworks and libraries (LangChain, LlamaIndex, OpenAI Function Calling, AgentKit, etc.).

Knowledge of agent architectures (reactive, planning, retrieval-augmented agents), and safe execution patterns.

Pipelines and data: Airflow/Kubeflow or similar; Spark/Flink; Kafka/Kinesis; strong data quality practices.

Microservices and runtime: Docker/Kubernetes, service meshes, REST/gRPC; performance and reliability engineering.

Model ops: experiment tracking, registries (e.g., MLflow), feature stores, A/B and shadow testing, drift detection.

Observability: OpenTelemetry/Prometheus/Grafana; debugging latency, tail behavior, and memory/CPU hotspots.

Cloud: AWS preferred (IAM, ECS/EKS, S3, RDS/DynamoDB, Step Functions/Lambda), with cost optimization experience.

Security/compliance: secrets management, RBAC/ABAC, PII handling, auditability.

Preferred Mindset

Product-oriented: You measure success by dealer and consumer outcomes, not just technical metrics.
Reliability- and safety-first: You move fast with guardrails, rollbacks, and clear SLOs.
Systems thinker: You design for multi-tenant scale, portability, and cost efficiency
Collaborative: You translate between Applied Sciences, Product, and the Data & AI Platform; you document and teach.

Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.

For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

Ready to apply?

Tekion

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Senior Software Engineer - (Machine learning Platform)

Tekion · Bengaluru, Karnataka, India

Apply now

Engineering Bangalore HQ Posted Apr 7, 2026

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

Senior Software Engineer - Senior Machine Learning Platform

Why This Role Matters

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.

What Makes This Opportunity Unique

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue. You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models .

Responsibilities

Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking.

Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics).

Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction.

Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning.

Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval.

Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows.

Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging.

Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance.

Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems.

Evolve the domain graph and entity resolution; build reliable data ingestion pipelines.

Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage.

Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost.

Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity.

Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls.

Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed.

Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices.

Desired Skills & Experience

5 - 7 years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems).

Production experience with Python plus one of Java/Scala/Go; microservices and API design.

MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka).

Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS.

Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows.

Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting.

Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry.

Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns.

Preferred Mindset

Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs.

Thinks in systems - observability, fallback, access control are core, not afterthoughts.

Passionate about AI - enjoys enabling real-world LLM and agentic use cases.

Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation.

Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience.

Documentation and teaching: you make complex systems understandable; you uplevel teams.

Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.

For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

Ready to apply?

Tekion

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Staff Data Scientist

project44 · Bangalore

Apply now

Engineering India - Bengaluru Posted Apr 7, 2026

Why project44?

At project44, we believe in better.

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk.

Description:  

project44 is looking for a Staff Data Scientist to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks. 

About the Role

Staff Data Scientist to lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

Experience 8–10+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
Experience with geospatial data, routing, and tracking systems
Experience with anomaly detection, fraud modeling, ETA prediction
Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

Deliver 2 high-impact ML capabilities with measurable customer value
Establish standardized experimentation, monitoring, and RCA workflows
Introduce GenAI/agentic capabilities that improve productivity and insight generation
Reduce time-to-production and increase reuse across DS teams
Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly.

Diversity & Inclusion

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day.

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture.

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application!

For any accommodation needed during the hiring process, please email  recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements.

More about project44

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences.

Ready to apply?

project44

View all jobs →

Staff Data Engineer

project44 · Bangalore

Apply now

Engineering India - Bengaluru Posted Apr 4, 2026

Why project44?

At project44, we believe in better.

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk.

Description:  

project44 is looking for a Staff Data Engineer to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks. 

About the Role

We are looking for a Staff Data Engineer to drive the execution and scaling of project44’s data platform.This role sits at the intersection of Data Engineering, Data Science, and Product, with a mandate to translate architectural vision into reliable, scalable systems used across teams.

You will partner closely with other data engineers to implement platform direction, establish engineering standards, and ensure consistent, high-quality execution across data systems. Your focus will be on solving complex data challenges, driving adoption of best practices, and enabling teams to build efficiently on a shared foundation.

As AI reshapes how data systems operate, you will also help integrate agentic and GenAI-powered workflows into data pipelines and developer workflows—improving automation, observability, and system intelligence.

What You’ll Do

Drive Platform Execution

Translate architectural direction into production-grade systems across ingestion, transformation, and serving layers.

Establish Standards & Best Practices

Define and enforce patterns for data modeling, pipeline design, observability, testing, and data quality across teams.

Solve Complex Data Problems

Own and resolve high-impact technical challenges related to scale, latency, reliability, and cost efficiency.

Enable Consistency Across Teams

Work across multiple teams to drive adoption of shared data models, tooling, and engineering practices.

Build Scalable Data Systems

Develop and optimize pipelines and data systems for performance, maintainability, and long-term scalability.

Integrate AI-Native Workflows

Implement agentic and GenAI-driven workflows to automate data operations, improve monitoring, and accelerate development.

Mentor & Raise the Bar

Act as a technical leader within the team, mentoring junior engineers and elevating engineering quality across the organization.

What We’re Looking For

8–10+ years in Data Engineering or Software Engineering, with a strong track record of building and scaling production-grade systems.

Technical Expertise

Strong programming skills (Python preferred, Java/Scala a plus) and deep experience with modern data technologies (Spark, Snowflake, Databricks).

Data Systems & Execution

Proven ability to build and operate reliable, scalable data pipelines and systems in production environments.

Data Modeling & Warehousing

Strong experience in data modeling, warehousing, and building analytics- and ML-ready datasets.

Distributed Systems & Trade-offs

Ability to navigate trade-offs across performance, cost, reliability, and scalability in cloud-native systems.

AI & Modern Tooling

Experience leveraging GenAI or agentic tools to improve developer productivity, automate workflows, or enhance data systems.

Cross-Team Influence

Experience working across teams to drive alignment, adoption of standards, and consistent execution.

Communication & Leadership

Strong communication skills and the ability to influence technical decisions across teams.

Preferred Skills

Experience with real-time and event-driven systems (Kafka, streaming architectures)
Familiarity with orchestration tools (Airflow, Argo) and containerization (Docker, Kubernetes)
Experience with data governance and access control (RBAC)
Exposure to analytics and BI tools (Looker, Tableau)
Experience building shared data platforms or internal tooling
Background in logistics, supply chain, or high-scale operational systems

What Success Looks Like (6–12 Months)

Successfully implemented core data platform patterns across multiple teams
Improved data reliability, observability, and quality in critical pipelines
Reduced inconsistency in data models and engineering practices across teams
Enabled faster development and deployment of data and ML workflows
Introduced AI-driven improvements in data workflows and developer productivity
Acted as a key technical leader, raising the bar for execution and engineering quality

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly.

Diversity & Inclusion

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day.

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture.

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application!

For any accommodation needed during the hiring process, please email  recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements.

More about project44

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences.

Ready to apply?

project44

View all jobs →

Staff Machine Learning Engineer

project44 · Bangalore

Apply now

Engineering India - Bengaluru Posted Apr 4, 2026

Why project44?

At project44, we believe in better.

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk.

Description:  

project44 is looking for a Staff Machine Learning Engineer to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks. 

About the Role

Staff ML Engineerto lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

Experience 8–10+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
Experience with geospatial data, routing, and tracking systems
Experience with anomaly detection, fraud modeling, ETA prediction
Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

Deliver 2 high-impact ML capabilities with measurable customer value
Establish standardized experimentation, monitoring, and RCA workflows
Introduce GenAI/agentic capabilities that improve productivity and insight generation
Reduce time-to-production and increase reuse across DS teams
Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly.

Diversity & Inclusion

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day.

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture.

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application!

For any accommodation needed during the hiring process, please email  recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements.

More about project44

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences.

Ready to apply?

project44

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Senior Data Scientist

project44 · Bangalore

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Engineering India - Bengaluru Posted Apr 4, 2026

Why project44?

At project44, we believe in better.

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk.

Description:  

project44 is looking for a Senior Data Scientist to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks. 

About the Role

Senior Data Scientist to lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

Experience 5+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
Experience with geospatial data, routing, and tracking systems
Experience with anomaly detection, fraud modeling, ETA prediction
Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

Deliver 2 high-impact ML capabilities with measurable customer value
Establish standardized experimentation, monitoring, and RCA workflows
Introduce GenAI/agentic capabilities that improve productivity and insight generation
Reduce time-to-production and increase reuse across DS teams
Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly.

Diversity & Inclusion

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day.

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture.

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application!

For any accommodation needed during the hiring process, please email  recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements.

More about project44

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences.

Ready to apply?

project44

View all jobs →

Data Engineer

OpenFX · Bengaluru (India)

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Engineering India - Bangalore Posted Apr 2, 2026

About Us

OpenFX is on a mission to move money as freely as data, unrestricted by time zones, banking hours, or legacy systems. We are building the infrastructure that will power the next generation of cross-border payment systems for institutions. The team's execution has been exceptional, and we're scaling at a remarkable pace. Our stellar early team comes with experience in companies like J.P. Morgan, Goldman Sachs, FalconX, Paypal, Affirm, Polygon, Kraken, Nium & others. We're backed by Accel, Faction, NfX, Accomplice, and other top-tier investors.

Role Overview

OpenFX processes billions of dollars in transaction volume across global corridors. Every decision around pricing, risk, liquidity, reconciliation, and compliance depends on accurate, timely, and trustworthy data. We need Data Engineers who can build reliable data pipelines, ensure data correctness end to end, and make data usable for analytics, risk, and operations at scale. You will own critical data infrastructure that directly powers our financial operations.

Key Responsibilities

Own 1 to 2 critical data pipelines that ingest, transform, and publish production data
Design data models that are accurate, auditable, and easy to consume
Build reliable ingestion pipelines from transactional systems and external partners
Ensure data correctness and freshness through validation, monitoring, and backfills
Handle late-arriving, duplicate, and inconsistent data safely
Partner with Backend, Analytics, Risk, and Ops teams to translate requirements into robust data solutions
Improve core data metrics such as pipeline reliability, data latency, and reconciliation accuracy
Automate pipeline operations including retries, recovery, and backfills

What We're Looking For

Required

3 to 7 years experience in data engineering or backend data systems
Strong SQL and data modeling fundamentals
Experience building batch and/or streaming pipelines
Experience working with relational databases and data warehouses
Experience handling schema evolution and backfills
Understanding of data quality, validation, and monitoring
Ability to clearly explain data tradeoffs

Preferred

Experience with Kafka, Spark, or Flink
Experience with modern warehouses (BigQuery, Snowflake, Redshift)
Experience with Airflow or similar orchestration tools
Experience in fintech or regulated domains
Familiarity with event-driven architectures
Experience mentoring junior engineers

What We Offer

Competitive salary and benefits package.
Equity in a rapidly growing company.
Opportunity to work in a fast-paced startup at the forefront of fintech innovation.
Opportunity to make a significant impact on global financial infrastructure.
Collaborative work culture with emphasis on personal and professional growth.

We are committed to building a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

Ready to apply?

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OpenFX

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Analytics Lead

OpenFX · Miami (USA), London (UK), Dubai (UAE), Bengaluru (India)

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Operations US - Miami India - Bangalore Remote UAE - Dubai UK - London Posted Apr 2, 2026

About Us

OpenFX is on a mission to move money as freely as data, unrestricted by time zones, banking hours, or legacy systems. We are building the infrastructure that will power the next generation of cross-border payment systems for institutions. The team's execution has been exceptional, and we're scaling at a remarkable pace. Our stellar early team comes with experience in companies like J.P. Morgan, Goldman Sachs, FalconX, Paypal, Affirm, Polygon, Kraken, Nium & others. We’re backed by Accel, Lightspeed, NfX and other top-tier investors.

Role Overview

We are seeking a talented Analytics Lead to build and lead our analytics function from the ground up. This role is crucial for establishing our core data infrastructure and delivering actionable insights across all teams to power strategic decision-making and drive business growth.

Key Responsibilities:

Data Infrastructure & Governance:

Design and implement our core analytics infrastructure, including data warehousing, ETL processes, and visualization tools.
Establish data quality standards, automate routine reporting, and create self-service analytics tools to ensure data accuracy and accessibility.

Business Intelligence & Insights:

Create and maintain dashboards for key business metrics across operations, finance, partnerships, and growth teams.
Develop comprehensive analytics for transaction monitoring, liquidity optimization, platform performance, and revenue forecasting.
Analyze user behavior and transaction patterns to drive growth strategies.

Risk & Financial Analytics:

Build analytics models for pricing optimization and financial planning.
Create risk monitoring systems and fraud detection analytics to ensure platform security.

Strategic Partnership & Team Leadership:

Partner with leadership to provide data-driven insights for strategic decision-making.
Build, manage, and mentor a high-performing team of analysts as the organization scales.

What we are looking for

Must-haves:

Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.
6+ years of experience in analytics or data science roles.
Strong programming skills in Python and SQL.
Experience with modern data stack tools (e.g., Snowflake, dbt, Airflow).
Proven experience building and maintaining large-scale data pipelines.
Excellent communication skills with the ability to present complex data to non-technical stakeholders.
Strong problem-solving skills and meticulous attention to detail.

What helps you stand out:

A Master's degree in a relevant field.
Experience in a fintech or financial services environment.
Direct experience with crypto/blockchain analytics.
Startup experience is highly preferred.
Expertise with data visualization tools like Tableau or Looker.

What We Offer

Competitive salary and benefits package.
Equity in a rapidly growing company.
Opportunity to work in a fast-paced startup at the forefront of fintech innovation.
Opportunity to make a significant impact on global financial infrastructure
Collaborative work culture with emphasis on personal and professional growth.

We are committed to building a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

Ready to apply?

Apply to OpenFX

OpenFX

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Director of Product Management, Data & Analytics

TRG Screen · Bengaluru, Karnataka, India

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Product Development Bangalore Posted Apr 1, 2026

Join TRG Screen: Building World-Class Teams. One Expert at a Time.

Are you ready to be part of a dynamic team at the forefront of subscription spend management innovation?

At TRG Screen, we're not just redefining how organizations manage their subscription expenses – we're shaping the future of the industry. With cutting-edge solutions and a commitment to excellence, we empower businesses around the globe to optimize their subscription investments and drive sustainable growth.

Join us in our mission to revolutionize subscription management and make a meaningful impact on the way businesses access and utilize critical information. At TRG Screen, your talent and ambition will find a home, where opportunities for growth and advancement abound.

About TRG Screen

TRG Screen is the leading provider of market data and subscription management technology and automation solutions, tailored to the unique needs of financial institutions and legal firms. Our integrated suite of solutions includes market data and subscription spend management, usage management, compliance reporting, and comprehensive managed services, which hundreds of clients worldwide use to remove cumbersome and inaccurate manual processes and gain control over market data and subscription costs at scale. For more than 25 years, TRG Screen has enabled businesses who rely on market data to monitor and strategically manage spending and usage of data and information services, including market data, research, software licenses, consulting and other necessary corporate expenses. TRG Screen solutions give decisionmakers full transparency into subscription spend and usage, enabling them to proactively manage subscription costs at scale, conduct more informed vendor negotiations, improve governance, and avoid unnecessary spending on these mission-critical business services. TRG Screen is headquartered in New York City, with offices in Europe and Asia, as well as a 24x7 client support center in Bangalore, India.

TRG Screen is a portfolio company of Vista Equity Partners, one of the world’s largest and most respected private equity firms.

JOB TITLE: Director of Product Management, Data & Analytics

LOCATION: Bangalore, India

REPORTS TO: Chief Product Officer

Th Role

TRG Screen is embarking on a strategic transformation of how data is accessed, consumed, and delivered across our product portfolio. Today, data lives within source and application databases — siloed, difficult to combine, and hard to expose to customers and internal teams. We are building a modern data lakehouse to change that, and we need a Director of Data Solutions to lead this journey.

This is a foundational, high-impact role. You will inherit a modern but underperforming data product, untangle legacy reporting built on stored procedures, and simultaneously set the vision and execution plan for the next generation of TRG Screen's data platform. You will serve as the senior data product leader for our product, engineering, and executive stakeholders.

This role is based in Bangalore, India, and begins as a senior individual contributor with a clear trajectory to build and lead a growing data product team.

Responsibilities

Stabilise & Improve the Current State

Take ownership of our existing data product — assess gaps, stabilise performance, and deliver near- term improvements that create immediate value for customers and internal teams.
Audit and rationalise a portfolio of legacy custom reports built on stored procedures — understand the business problems they solve, document them, and define a clear migration path.

Define the Data Lakehouse Vision

Define the vision and roadmap for TRG Screen's data lakehouse, grounded in deep customer research and a clear understanding of where data solutions deliver the most value.
Apply a Jobs to Be Done framework to uncover what customers are truly trying to accomplish and translate those insights into a prioritised product backlog.
Conduct ongoing customer discovery with clients and customer-facing teams (Customer Success, Sales, Professional Services) to ensure the roadmap reflects real customer pain and opportunity.
Work closely with the Data Architect and Database Engineer to communicate requirements clearly . You define the what and why; they own the how.
Champion an AI-first approach to visualisation and insight delivery, evaluating and selecting third-party AI tooling rather than building bespoke visualisation layers.

Build & Deliver Data Products

Define and ship customer-facing data products — including APIs, datasets, and consumption layers that customers or customer-serving teams directly use and derive value from.
Productise TRG Screen's data as a revenue stream — define how data and APIs are packaged, tiered, and commercialised for customers and partners.
In partnership with product stakeholders, own the API product strategy — defining APIs not just as technical interfaces but as sellable, scalable products with clear value propositions, entitlement models, and a developer experience that delights customers.
Partner with engineering to translate customer-driven requirements into clear, actionable briefs.
Ensure data quality, governance, reliability, and documentation across all data products.

Own the AI Data Strategy

Serve as the product owner of TRG Screen's AI data foundation — defining what data needs to be available, in what form, and to what quality standard to power AI and ML workloads.
Use customer research and Jobs to Be Done methodology to define intelligence layer product requirements; what AI-powered features and experiences customers need, handed off to technical teams for execution.
Collaborate with TRG Screen's AI strategy stakeholders to align the data product roadmap with AI product priorities.
Champion AI-first approaches to data consumption: evaluating and recommending AI-powered visualisation and insight tools.

Lead & Grow the Team

Begin as a senior individual contributor with direct leadership responsibility — you will be the data product function at TRG Screen initially.
Work in close partnership with a Database Engineer and Data Architect, providing product direction and prioritisation while they drive implementation.
Build out your team as the platform matures, with a planned trajectory to hire and lead a Product Manager and Product Owner.
Act as a player-coach: credible enough to go deep on architecture and technical decisions alongside engineering peers, while driving strategy and stakeholder conversations at the executive level.

Skills and Qualifications

Required Qualifications

8+ years of experience in data product management or related roles, with at least 3 years in a leadership capacity.
Deep expertise in Jobs to Be Done and customer discovery — ability to uncover what customers truly need from data and translate that into a compelling product roadmap.
Strong product instincts — knows how to prioritise ruthlessly, write clear requirements, and drive a backlog in an Agile environment.
Solid working knowledge of data concepts (SQL, data modelling, APIs, ETL/ELT, BI tools), enough to be a credible partner to a Data Architect and Database Engineer.
Experience defining and shipping data APIs as commercial products — including packaging, entitlements, and usage-based models.
Understanding of data monetisation strategies — how to turn data assets into revenue-generating products.
Strong understanding of AI and ML data requirements — how to define product needs for AI-powered features and intelligence layers.
Familiarity with LLMs, generative AI, and AI-powered product surfaces — and how they consume and depend on structured, high-quality data.
Strong stakeholder management skills — able to translate between engineering, product, and executive audiences.

Preferred Qualifications

Familiarity with Power BI source integration or similar third-party BI connectivity.
Exposure to AI-powered analytics or visualisation tooling.
Experience with dbt, Airflow, or modern data orchestration tools.
Background in a SaaS or multi-product environment where data is fragmented across systems.
Prior experience in financial data, market data, or fintech — relevant to TRG Screen's domain

Join TRG Screen and unlock your potential in an environment where innovation thrives, opportunities abound, and your contributions make a difference. We are an equal opportunities employer. We recognise and value the power of diversity in our workplace and are committed to being an employer of choice for everyone. We welcome and encourage applicants from all backgrounds. All applications for employment are considered strictly on the basis of merit.

At TRG Screen, we understand that diverse and inclusive teams are not just beneficial, they are essential to our success. We recognize that embracing diverse perspectives, backgrounds, and experiences fosters innovation, enhances problem-solving capabilities, and drives better business outcomes. By cultivating a culture of inclusion where every voice is heard and valued, we empower our world class teams to thrive, excel, and drive positive change.

We are proud of our diverse workforce and are dedicated to creating a safe and welcoming environment for all employees. People from various ethnicities, ages, genders, and abilities are encouraged to apply.

Ready to apply?

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Staff Software Engineer (Data Platform)

Arcana Analytics · Bangalore, Hybrid

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Engineering Arcana Analytics Posted Mar 28, 2026

Staff Software Engineer (Data Platform)
Join our dynamic team at the forefront of cutting-edge technology as we seek a seasoned Staff Data Engineer. Embark on a journey where your deep-rooted expertise in distributed systems, data architectures, and large-scale processing becomes the cornerstone of building high-performance data platforms. This pivotal role demands proficiency in designing and scaling compute and I/O-intensive data systems, ensuring reliability, efficiency, and cost optimization across the data lifecycle.

Responsibilities:
● Design and build scalable data platform components for batch and real-time data processing.
● Architect, develop, and operationalize large-scale data systems across ingestion, transformation, and serving layers.
● Build and manage robust data pipelines ensuring high reliability, scalability, and cost efficiency.
● Develop reusable frameworks and tooling to accelerate productivity for data engineers and data scientists.
● Leverage expertise in Python, Airflow, SQL, and cloud platforms to build production-grade data solutions.
● Optimize query performance and data models using strong understanding of columnar OLAP systems such as ClickHouse, Doris, and StarRocks.
● Implement streaming and near real-time data processing systems.
● Translate complex business requirements into scalable and efficient data platform solutions.
● Work collaboratively with cross-functional teams and provide technical leadership and mentorship.
● Drive architectural decisions by evaluating tradeoffs and selecting the right tools for the problem.

Requirements:
● Bachelor's Degree in Computer Science, Information Technology, or a similar discipline.
● 8+ years of professional experience in data engineering, backend systems, or distributed systems.
● Proven experience building scalable data platforms and large-scale data systems.
● Strong experience with ETL pipelines, data integration, and workflow orchestration systems such as Airflow or Temporal.
● Hands-on experience in Python and SQL with strong understanding of data warehouse concepts.
● Experience working with distributed OLTP/OLAP databases such as ClickHouse, PostgreSQL, Cassandra, or Elasticsearch.
● Knowledge of messaging and streaming systems such as Kafka.
● Experience with cloud platforms (AWS/GCP) and big data tools such as Spark.
● Strong understanding of columnar storage systems and query optimization techniques.
● Solid understanding of distributed systems fundamentals and associated tradeoffs.
● Experience working with containers and orchestration tools such as Docker and Kubernetes.
● Strong Linux fundamentals and system-level debugging skills.
● Familiarity with modern data architectures such as Lakehouse (Iceberg, Hudi, Delta) is a plus.

Ready to apply?

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Arcana Analytics

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Software Engineer II - (Machine Learning Platform)

Tekion · Bengaluru, Karnataka, India

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Engineering Bangalore HQ Posted Mar 26, 2026

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

Why This Role Matters

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.

What Makes This Opportunity Unique

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue. You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models .

Responsibilities

Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking.

Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics).

Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction.

Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning.

Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval.

Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows.

Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging.

Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance.

Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems.

Evolve the domain graph and entity resolution; build reliable data ingestion pipelines.

Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage.

Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost.

Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity.

Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls.

Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed.

Desired Skills & Experience

4 - 5+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems).

Production experience with Python plus one of Java/Scala/Go; microservices and API design.

MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka).

Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS.

Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows.

Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting.

Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry.

Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns.

Preferred Mindset

Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs.

Thinks in systems - observability, fallback, access control are core, not afterthoughts.

Passionate about AI - enjoys enabling real-world LLM and agentic use cases.

Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation.

Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience.

Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.

For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

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Tekion

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Senior Software Engineer (Machine Learning Platform)

Tekion · Bengaluru, Karnataka, India

Apply now

Engineering Bangalore HQ Posted Mar 26, 2026

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

Why This Role Matters

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.

What Makes This Opportunity Unique

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue. You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models .

Responsibilities

Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking.

Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics).

Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction.

Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning.

Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval.

Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows.

Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging.

Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance.

Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems.

Evolve the domain graph and entity resolution; build reliable data ingestion pipelines.

Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage.

Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost.

Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity.

Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls.

Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed.

Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices.

Desired Skills & Experience

5+ - 8+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems).

Production experience with Python plus one of Java/Scala/Go; microservices and API design.

MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka).

Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS.

Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows.

Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting.

Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry.

Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns.

Preferred Mindset

Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs.

Thinks in systems - observability, fallback, access control are core, not afterthoughts.

Passionate about AI - enjoys enabling real-world LLM and agentic use cases.

Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation.

Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience.

Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.

For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

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