We're seeking a Head of Machine Learning to own and scale the ML function at Prodigal. This is the senior-most ML role in the company — partnering directly with the CTO as a peer technical leader, defining the multi-year ML vision, building and leading a world-class team, and translating cutting-edge research into production systems that move the needle for over 100 customers and millions of consumers. You'll set the bar for technical excellence, hire and develop the next generation of ML leaders, and shape what consumer finance intelligence looks like over the next decade. If you've operated at this level before — or are ready to step into it at a company where ML is the engine of the product — we want to talk.

Responsibilities:

• Own the ML function end-to-end — vision, roadmap, team, delivery, and measurable business impact across classical ML, NLP, GenAI, and Agentic AI
• Partner with the CTO as the senior ML leader to set company-wide technical direction and shape the long-term roadmap for Prodigal's Intelligence Engine
• Build and lead a high-performing ML organization — hire, mentor, and develop ML engineers, applied scientists, and tech leads across multiple pods
• Translate research into product — drive the application of LLMs, Agentic AI, the modern NLP stack, recommendation systems, and classical ML into production systems serving 100+ customers
• Set technical standards for model development, deployment, monitoring, evaluation, and experimentation that scale across the org
• Architect data and ML infrastructure in partnership with the platform and engineering teams to support large-scale training and reliable, low-latency inference
• Communicate strategy and outcomes clearly to the founders, board, customers, and broader engineering organization
• Represent Prodigal externally — at conferences, in research collaborations, and as a senior voice in the consumer finance AI community
• Stay at the frontier of ML and GenAI research, identifying where new techniques unlock product and business advantage
• Collaborate cross-functionally with product, engineering, GTM, and customer success leaders to ensure ML investment ties directly to revenue, retention, and customer outcomes

Requirements:

• 10+ years of experience in machine learning and software development at a tech or product company, with 4+ years leading ML teams (managing engineers and/or tech leads)
• Proven track record of shipping ML products in production at scale with measurable business impact
• Deep technical fluency across classical ML, deep learning, and the modern NLP/LLM stack — you can still go deep in design reviews, not just review at the surface
• Strong coding skills in Python. Hands-on with PyTorch, scikit-learn, Pandas, and Spark
• Demonstrated success hiring, mentoring, and growing ML talent — including team leads and senior engineers
• Strong executive communication and the ability to set technical direction with founders, peers, and the board
• A bias for outcomes — you connect model work to revenue, engagement, and operational metrics

Preferred Qualifications:

• Experience as a founding ML hire, ML lead, or applied science leader at a high-growth AI/ML product company
• Background in voice AI, conversational AI, speech, NLP on unstructured text, or fintech/lending domains
• Experience with cloud services (AWS), Databricks, and building scalable, distributed systems
• Track record of running A/B testing and experimentation programs at scale
• Patents, publications, or open-source contributions; strong institutional pedigree (IIT, BITS, NIT, IISc)
• Experience scaling an ML org through a hypergrowth phase

Job Benefits

• GenAI at the core – Lead the ML function at a company where AI isn't a feature, it's the product. Shape groundbreaking work that redefines consumer finance intelligence.
• World-class team - You'll get the chance to learn from (and teach) some of the brightest and most skilled people you'll ever meet. Our team members have been part of BCG, Deloitte, EY, Blackstone, Meta, Amazon and are IIT, IIM, BITS alumnus.
• Continuous education - As relentless seekers of knowledge, we sponsor and support any training materials, books, courses, and exam fees for upskilling yourself in areas related to your role - but that's not where it ends. If you make a good case for some extra learning, we're delighted to foot the tab.
• Food at the office – Meals are on us. We won't let your stomach grumble while you hustle.
• Health insurance - Health always comes first. The health of your family is as important to us as it is to you. We offer insurance coverage for both you and your family.
• Flexible schedule - We're not a "clock in, clock out" company. Morning person? Start work while the world's still sleeping. Night owl? Ramp things up while others are winding down. You're fully trusted to create the right conditions for your own personal peak productivity. We only ask that you be available to your teammates for seamless collaboration.
• Generous leave policy - Take all the time you need to recharge your batteries - no cap on vacation here. Because a rested, relaxed, and refreshed mind is a happy and effective mind.
• Recreation & team activities – We regularly indulge in friendly football, table tennis, cooking sessions, and challenge each other to do those extra push-ups or chug that 4th drink (of course, that's Nimbu Pani).

Meet Sangram (Cofounder and CTO) and hear his vision for Prodigal: https://www.youtube.com/embed/FTWlN9fwiIA?feature=shared

About Inizio Ignite:

Inizio Ignite is the global advisory partner for health and life sciences, encompassing connected expertise across Research Partnership, Putnam, Vynamic, and STEM. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health.

Company Descriptor

Inizio Ignite is the global advisory partner for health and life sciences, encompassing connected expertise across Research Partnership, Putnam, Vynamic, and STEM. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health. Our Research Partnership healthcare market research team provides research and insights to inform and power healthcare decisions. Serving a variety of clients across the lifecycle, our expertise includes data, research & insights (proprietary syndicated and custom research) and brand tracking (ATU). Proudly part of Inizio – the market-leading commercialization partner for health and life sciences. From early-stage development to loss of exclusivity, we simplify complexity, unlock value, and make collaboration seamless at every pivotal moment – supporting confident, insight-driven decisions that move innovation forward. 

Role Overview

The Data Delivery & Dashboards Executive role will report into the Dashboard Manager. The Data Delivery & Dashboards Executive will be a key member of the newly formed India-based Data Management & Delivery Hub, supporting quantitative healthcare market research projects across global markets. As a Dashboard Developer Executive, you build and maintain high impact dashboards and data visualizations that transform raw market research data into actionable insights. You’ll collaborate with researchers, analysts, and engineers to ensure data flows seamlessly from collections to visual storytelling. You will also support the team in delivering insightful, user-friendly dashboards through automated tools and off-the-shelf solutions. This is a fantastic opportunity to develop your skills in data management, quality assurance, and data visualisation, while working alongside an experienced team in a dynamic, global environment. Skill Set required

What you'll be doing

Brand Equity tracking support with our in-house platform:

• Maintain the pipeline for the project data process flow (this includes receival of data into in-hosue Tool, through the data processing stage into the storage mart, through the python utilities into required outputs)
• Maintain and update python utilities when required due to changes from the research team
• Manage and rectify when failures occur in the pipeline, liaising with both the data providers, research team and developers on the dashboard
• Manage the storage mart and data warehouse
• Support team with edits in-house platform

Data Quality Checks:
Assist in performing detailed quality control checks on large and complex datasets to ensure accuracy, completeness, and consistency.

Data Transformation & Standardisation:
Support the transformation and standardisation of data files to align with internal data structures, project needs, and client-specific formats.

Dashboard Support & Maintenance:
Assist in the creation, population, and maintenance of dashboards using off-the-shelf tools (e.g., Power BI, Tableau, or similar platforms), ensuring outputs are clear, accurate, and aligned with research objectives.

Data Delivery Management:
Help manage and organise the final delivery of data files and dashboards to internal teams and clients, ensuring timely and error-free execution.

Collaboration Across Teams:
Work closely with internal stakeholders including Development team, Data Processing, Scripting, Project Management and Research teams to ensure smooth handovers and integration of deliverables.

Documentation & Reporting:
Maintain clear documentation of processes, data transformation steps, and QC logs to support transparency, reproducibility, and audit-readiness.

Continuous Learning & Development:
Engage in training opportunities to build knowledge in healthcare data, market research workflows, dashboarding tools, and data handling best practices.

What you'll need

Your skills and experience:

Technical Expertise

• Atleast 5+ years expertise in languages like Python and SQL.
• Mastery in advanced Core Python (generators, decorators, OOP, async programming), architecture design.
• Proficient in libraries like Pandas - Joins, Melting, handling missing values, NumPy, TensorFlow etc.
• Proficient in SQL (PostgreSQL, MySQL).
• Understanding MVC/MVT, microservices, and system design principles.
• Experience in setup of data pipelines is highly desirable.
• Knowledge of high-performance framework (Django, FastAPI, Flask) is a plus.
• Cloud platform expertise (AWS, Azure, GCP), and building ETL/ELT pipelines.
• Experience in version control system.

Ideal candidate should be

• You are proactive, dedicated and enthusiastic, with a ‘can do’ attitude and approach
• You demonstrate a high level of accuracy and attention to detail, as well as strengths in organisation and prioritisation
• You are a collaborative team player who works well with colleagues
• You communicate ideas and issues in an effective, straightforward fashion
• Logical thinking and ability to troubleshoot errors or discrepancies in tabulated data.
• Ability to interpret tabulation specifications and apply them accurately.
• Problem-solving skills (particularly relating to situations requiring analytical judgement and establishing best practice solutions)
• You are highly motivated and want to seize opportunities to develop new skills and progress your career

Artificial Intelligence

Inizio may use AI technologies to support certain aspects of our recruitment process, but all hiring decisions are made by our human recruiting team. We are committed to fair, inclusive, and human-led hiring practices. Don't meet every requirement? That's okay! We are dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others.

Secure Every Identity, from AI to Human

Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.

This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.

Okta seeks a skilled Staff Full Stack Engineer with expertise in NetSuite and/or  Oracle Fusion Cloud Applications. As part of our Business Technology team, you will be responsible for developing and optimizing full-stack solutions, including custom scripts, workflows, integrations, and system enhancements for both NetSuite and Oracle Fusion to improve business processes and scalability. This role will report to the Manager in Bangalore, India. We’d love to hear from you!

Job Duties and Responsibilities

• Design, develop, and maintain full-stack solutions for Finance Tech stack like NetSuite, Coupa and Oracle Fusion Cloud Applications etc., using any of the full-stack applications like Node Js/React
• Develop and maintain robust off-platform integration scripts using Python & LangChain to manage data transfer and interactions between NetSuite (via SuiteTalk or RESTlets) and AI Platforms
• Architect and implement scalable, secure, and cost-efficient cloud-native solutions on AWS for RAG, MCP, and Agentic AI (LangGraph) 
• Closely work with the BT Product Manager to design, develop, test, implement & support system solutions primarily in Finance Technology
• Provide technical consultation, best practices, and problem resolution for AI and Agentic AI for the Finance tech stack NetSuite, Oracle Fusion, and associated integrated systems
• Support & resolve production issues across the full application stack
• Develop and maintain integrations with third-party applications via REST/SOAP APIs
• Design and implement custom Generative AI solutions using the SuiteScript Generative AI API for practical NetSuite use cases and explore similar capabilities in Oracle Fusion

Required Skills:

• 9+ years in Python and its libraries (e.g., Pandas, Boto3) for data manipulation, ETL processes, and developing serverless functions to interact with foundational AI services on platforms like AWS Bedrock.
• Deep hands-on experience with AWS solutioning, including designing and deploying production applications using core services such as AWS EC2, AWS Lambda, Amazon S3, Amazon RDS, and API Gateway. Familiarity with Infrastructure as Code (IaC) tools like CloudFormation or Terraform is essential.
• Proficiency in NetSuite development experience (SuiteScript, SuiteFlow, SuiteTalk).
• Experience with SuiteCloud tools, REST/SOAP APIs, and third-party integrations.
• Experience with the SuiteScript Generative AI APIs to integrate LLM capabilities for advanced scripting solutions
• Strong understanding of Finance Business processes (Order Management, Billing, Vendor bill, etc.).
• Proficiency in JavaScript, SQL, and related web technologies
• Configure NetSuite modules to align with business needs, including leveraging Prompt Studio to customize and manage NetSuite AI functions like Text Enhance.
• Ability to drive and architect solutions with other developers, focusing on maximizing the value of embedded NetSuite AI capabilities
• Working Experience on the MCP and familiar with SaaS MCP connectors, like NetSuite MCP or similar
• Working experience with foundational AI services, with a desire to use a unified platform like AWS Bedrock for Generative AI development and deployment
• Nice to have some core Amazon Machine Learning (ML) services, specifically AWS SageMaker (for building, training, and deploying custom ML models), AWS Comprehend (for natural language processing and text analytics), and  Retrieval Augmented Generation (RAG)

Education and Certifications

• A Bachelor’s degree in Computer Science, Information Systems, or equivalent years of industry experience
• AWS cloud Certification or any ERP foundation certificate is a plus

#P16568_3435773
#LI_Hybrid

The Role:

• As an Applied Value Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

The work you’ll do:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Applied AI Solution Engineer stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Solution Engineers specialize in domains (e.g. supply chain) and industries

The qualifications you need:

• 3-5 years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

Why we're hiring:

As a Data Engineer in the WPP Enterprise Data Group, you will be responsible for the design and implementation of scalable data solutions providing enterprise-scale data transformation across a broad range of projects.

Your role will focus on delivering solutions that utilize large-scale data ingestion, processing, storage/querying, streaming, and batch analytics using Databricks. As part of a team, you will implement world-class solutions designed by our data architects. Your responsibilities will include estimating, designing, coding, testing, deploying, and ensuring scalability and performance on Azure using key technologies like Databricks.

As a hands-on technologist with an extensive data engineering background using Databricks, you will be joining a group of Data Engineers who are passionate about building the best possible solutions for our business and endorse a culture of life-long learning and collaboration.

What you'll be doing:

• Design, build, test and maintain data pipelines (ELT), according to business and technical requirements.
• Implement secure platforms with data governance in mind.
• Play a key role in automation and building industry leading solutions against architectural best practices.
• Propose technical designs and develop integrations.
• Deliver data migrations between legacy & modern platforms
• Design & deliver data warehousing solutions and key data engineering workstreams for any required solution.
• Support cross-functional teams across the data space.

What you'll need:

Minimum requirements for this role include:

• 3+ years of experience designing and building scalable distributed data pipelines and dimensional data models
• 3+ years of experience in Python and SQL
• Experience using Databricks platform and PySpark is a must.
• Extensive experience of Microsoft Azure data services – Data Factory, ADLS gen2, Event Hubs, Azure SQL, Azure Key Vault
• Ideally experience in the following – Kafka, Delta Lake, Pandas
• A demonstrable understanding of Continuous Integration, Continuous Delivery (CI/CD) and Agile practices, unit & integration tests and development practices using Azure DevOps.
• Fluency in English.
• Exposure to AI & ML technologies is a plus.

Who you are:

You're open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.

You're optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected.

You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.

What we'll give you:

Passionate, inspired people – We aim to create a culture in which people can do extraordinary work.

Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry.

Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge?

#LI-Hybrid 

Job Title: GenAI Developer/ Engineer

About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

Location - Bangalore

Experience - 6 to 10

Skills and Qualifications:

Preferred skills:

Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy)

GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic Kernel

Machine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch

Key Responsibilities:

• Develop scalable Python applications focused on GenAI
• Knowledge of Snowflake Cortex is a big plus.
• Learn and apply techniques like document chunking and embeddings
• Proficient in both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization.
• Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs
• Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
• Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
• Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
• Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
• Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
• Work with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)
• Design and implement scalable RESTful APIs and microservices to expose AI functionalities
• Deploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)
• Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle management
• Follow coding best practices and contribute to testing and documentation
• Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
• Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
• Communicate effectively with both technical and non-technical team members, ensuring alignment and understanding across all project phases.

Opportunity Overview:

We are seeking a Technical, Hands-on Manager to lead a team in building AI-driven healthcare enterprise applications. In this role, you will combine strong people leadership with deep technical expertise to guide the development of scalable, data-intensive solutions that drive meaningful business impact.

As a leader who is still technically involved, you will mentor and manage data scientists and analysts while having the ability to guide the team through evaluating, selecting, and implementing the right models, paired with an understanding of end to end workflow and ensure the delivery of scalable AI solutions. 

This position requires excellent communication and collaboration skills as you partner closely with internal stakeholders and cross‑functional engineering, product, and clinical teams. In our fast-paced environment, adaptability is key—your ability to reprioritize quickly and lead your team through evolving business needs will ensure maximum impact

What you’ll do:

• Lead, mentor, and develop a high‑performing team of Data Scientists and ML Engineers, ensuring strong execution and continuous skill advancement.
• Contribute to event‑driven architecture design and implementation, enabling asynchronous processing and large‑scale system integration.
• Work seamlessly across functions—partnering with Data Scientists on model tuning, experimentation, and prompt design; collaborating with Product and Software Engineering to embed AI/ML into user-facing applications; engaging with DevOps/Platform Engineering on environment setup, CI/CD, monitoring, and reliability; and working with Data Engineering on pipeline design and ingestion strategies.
• Provide technical leadership in the effective use of AWS services such as Lambda, EC2, EMR, S3, Athena, Batch, Textract, Comprehend, Bedrock.
• Drive the implementation of project scope definition, effort estimation, and planning in close coordination with cross-functional teams.
• Conduct code reviews, provide architectural direction, and champion SDLC best practices, while balancing leadership responsibilities with hands‑on technical contributions to ensure timely, high‑quality delivery.

Required Qualifications:

• 7+ years of overall professional experience delivering data-driven AI/ML-focused solutions. 3+ years of direct team management experience, leading Data Scientists, ML Engineers, or similar technical roles.
• Hands-on experience in Python with strong proficiency in libraries such as Pandas, NumPy, SciPy, Matplotlib, and regular expressions. Advanced SQL querying and optimization for large datasets.
• Practical experience in training, tuning, and testing ML algorithms (e.g., SVM, CART, Bagging, Boosting) and text mining techniques; familiarity with modern ML/DL approaches.
• Experience with prompt engineering and leveraging GenAI for classification, data enrichment, semantic embeddings, and innovative AI-driven solutions.
• Experiment and rapidly prototype design frameworks, validate hypotheses efficiently, and iterate on AI/ML models to support fast-paced development.
• Strong knowledge of Object-Oriented Programming (OOP) and experience creating custom Python packages for serverless applications.
• Hands-on experience with AWS services including Lambda, EC2, EMR, S3, Athena, Batch, Textract, and Comprehend.
• Work seamlessly across Data Science, Engineering, Product, DevOps, and Data Engineering teams to align technical decisions with business goals, ensuring smooth integration of AI/ML capabilities into production systems
• Excellent communication and storytelling skills, capable of translating complex AI/ML concepts into clear, actionable insights for leadership, stakeholders, and non-technical partners.
• Ownership mindset with end‑to‑end accountability, ensuring delivery from concept to deployment to monitoring—while continuously identifying risks, blockers, and opportunities for improvement.

Good to have:

• Background in healthcare payment integrity, clinical data workflows, or payer/provider analytics.
• Strong thought leadership in AI/ML, including guiding stakeholders on feasibility, risk, architecture, and adoption strategy.
• Prior experience in deploying LLM‑powered production features,optimize prompting strategies, transforming experimental prototypes into robust, scalable services delivered through well‑defined APIs.
• Familiarity with compliance, governance, and security best practices for healthcare data (HIPAA, PHI handling, logging, auditing).

Ability to commute/relocate:

• Nacharam, Hyderabad, Telangana*: Reliably commute or planning to relocate before starting work (Preferred)

Interview Process*:

1. Connect with the Hiring Manager for a Preliminary Phone Screening
2. Behavioral Interview(s)
3. Case Study
4. Interview with Senior Leadership

*Subject to change

About Cohere Health:

Cohere Health’s clinical intelligence platform delivers AI-powered solutions that streamline access to quality care by improving payer-provider collaboration, cost containment, and healthcare economics. Cohere Health works with over 660,000 providers and handles over 12 million prior authorization requests annually. Its responsible AI auto-approves up to 90% of requests for millions of health plan members.

With the acquisition of ZignaAI, we’ve further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate™, an AI-driven clinical and coding validation solution that operates in near real-time. By unifying pre-service authorization data with post-service claims validation, we’re creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures providers are paid promptly and accurately.

Cohere Health’s innovations continue to receive industry wide recognition. We’ve been named to the 2025 Inc. 5000 list and in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024. Backed by leading investors such as Deerfield Management, Define Ventures, Flare Capital Partners, Longitude Capital, and Polaris Partners, Cohere Health drives more transparent, streamlined healthcare processes, helping patients receive faster, more appropriate care and higher-quality outcomes.

The Coherenauts, as we call ourselves, who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone.

We can’t wait to learn more about you and meet you at Cohere Health!

Equal Opportunity Statement: 

Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all.  To us, it’s personal.

Job Title: QA Data Engineer

Location: Any Orion Innovation office in India(Pune/Mumbai/Kochi/Coimbatore/Chennai/Hyderabad)

Work type: Hybrid 

Role Description / Responsibilities

A technically skilled QA professional specialising in validating data platforms, ETL pipelines, analytical models, and large‑scale data transformations. The QA Engineer works closely with developers, data engineers, product teams, and business SMEs to ensure the quality, reliability, and accuracy of data assets across the delivery lifecycle. of our digital data audit products.

Core Responsibilities

Data Testing & Quality Assurance

• Design, develop, and execute test plans for data & analytics products, including ingestion pipelines, transformations, data models, and dashboards.
• Apply robust testing techniques for data completeness, consistency, accuracy, timeliness, and lineage.

Technical & Platform Responsibilities

• Write and execute SQL/PL‑SQL queries for data verification, profiling, and root‑cause analysis.
• Use Databricks to inspect data, validate notebook logic, execute test scripts, and investigate transformation failures.
• Work with Delta Lake, Spark DataFrames, and related components to test scalable data processing.

ETL/ELT and Pipeline Testing

• Validate end‑to‑end ETL/ELT workflows.
• Ensure correctness of data transformations and seamless movement between data layers.
• Conduct regression testing following schema evolution, code updates, or pipeline refactoring.

Collaboration & Delivery Practices

• Work closely with Data Engineers, Developers‑in‑Test, Business SMEs, and Product Owners to ensure high‑quality delivery.
• Provide clarity on data issues, identify root causes, and support resolution.
• Participate in refinement sessions to assess testability of new features and data logic.
• Contribute to automation frameworks, promoting continuous integration of data tests.

Automation & Scripting (Desirable)

• Develop automated test scripts using Python, PySpark, or Pandas.
• Contribute to automated test frameworks that validate transformations and data quality at scale.

Skills & Experience

Mandatory

• Proven experience testing data and analytics platforms.
• Advanced SQL and PL/SQL skills.
• Hands‑on experience with Databricks (notebooks, Delta Lake, Spark).
• Strong understanding of ETL concepts and data transformation methodologies.
• Experience validating large datasets, data pipelines, and data models.

Desirable

• Python for test automation and data manipulation.
• PySpark for distributed data testing.
• Pandas for lightweight automation and exploratory validation.
• Exposure to CI/CD, data observability tools, or version control (Git).

Job Summary

As a Data Scientist, you will work within a cross-functional agile team contributing to the company's growth in a fast-moving environment. You will develop new tools and features by working closely with engineers, product managers, designers, and engineers. Ultimately, the goal is to help our users make smarter decisions. On top of that, you’ll have the support of a diverse, large team of data scientists working across all Brandwatch products to support your technical and career development. This role is open to people with a variety of professional and academic backgrounds and you can expect to develop your skills in a wide variety of techniques, including machine learning, statistical modelling, and computational linguistics.

Essential Duties and Responsibilities

Work with stakeholders to clarity and refine questions.

Collect, clean, and prepare data, generally this will be large volumes of text along with metadata and will often need to be handled with big data tools.

Build models to solve a range of different problems, such as text classification and clustering, automated insight generation, and time series analysis.

Develop evaluation methodologies, which will vary from those based around conventional classification metrics (such as precision and recall), to designing methods to evaluate how well your tool helps a user achieve a defined task.

Support engineers as your projects are shipped. Sometimes you will also help maintain and upgrade the tools and technologies you develop.

Perform other duties as required to support evolving business needs.

Minimum Required Qualifications

A good working knowledge of Python (or another modern programming language, with willingness to learn Python).

A solid understanding of statistics and/or machine learning.

Enjoy an experimental and iterative approach to building products.

An ability to communicate with non-technical stakeholders, or willingness to skill up in this area.

Preferred Qualifications

Working in a data science team.

Common data science libraries, such as Numpy, Scipy, Pandas, SKlearn, Spacy.

Big data tools, such as: Spark, Dask, MapReduce, or alternatives.

Cloud computing, for example: AWS EC2, S3.

Linux style shell commands.

Application prototyping frameworks such as Dash, or Shiny.

As a Staff Data Scientist, you will act as a senior technical leader and trusted advisor across multiple teams. You’ll guide stakeholders through the complexity of modern AI systems, with a particular focus on agentic AI architectures (including LangGraph, LangFuse, and related tooling), as well as broader machine‑learning strategy. This role blends deep technical expertise, consultative problem‑solving, and cross‑functional leadership. 

You will often support several initiatives simultaneously, helping teams understand feasibility, scope, and risk while shaping high‑impact AI solutions that align with business needs. You’ll also mentor junior colleagues, elevate data‑science practices, and contribute hands‑on to the development of production‑grade AI systems. 

What you'll do:

AI Consulting & Advisory 

• Partner with product, engineering, and business teams to translate ambiguous problems into clear AI opportunities. 

• Provide expert guidance on agentic AI, including workflow orchestration, evaluation, observability, and safety. 

• Assess the complexity, feasibility, and expected value of proposed AI initiatives, helping teams prioritise effectively. 

• Communicate trade‑offs, risks, and solution paths to both technical and non‑technical audiences. 

AI & ML Solution Design 

• Architect end‑to‑end AI systems that solve real business problems, from early discovery through deployment. 

• Design agent‑based workflows, retrieval‑augmented pipelines, and ML‑powered automation. 

• Define evaluation strategies, data requirements, and success metrics for AI features and products. 

• Collaborate with engineering teams to ensure solutions are scalable, maintainable, and aligned with platform strategy. 

Hands‑On Technical Work 

• Build prototypes, proof‑of‑concepts, and production‑ready components using Python, modern AI frameworks, and cloud tooling. 

• Develop and refine agentic AI workflows using LangGraph, LangChain, LangFuse, or similar frameworks. 

• Implement machine‑learning models, retrieval systems, and data pipelines where needed. 

• Contribute to internal libraries, tooling, and best practices for AI development. 

Leadership & Mentorship 

• Mentor junior and mid‑level data scientists, providing guidance on modelling, experimentation, and system design. 

• Lead technical discussions, design reviews, and cross‑team collaboration sessions. 

• Champion high standards for code quality, documentation, and reproducibility. 

• Help shape the long‑term AI strategy and technical roadmap, through your technical knowledge on the art of the possible, and the business problems our clients face. 

What you'll bring:

• Extensive experience in data science, machine learning, or applied AI, including hands‑on coding in Python and common data science libraries, such as Numpy, Scipy, Pandas, SKlearn, Spacy. 

• Ability with prototyping frameworks such as Dash. 

• Good working understanding of code version control with Git. 

• Experience with big data tools, such as: Spark, Dask, or alternatives. 

• Strong understanding of agentic AI, orchestration frameworks, and LLM‑based system design. 

• Ability to evaluate project complexity, identify risks, and guide teams toward pragmatic solutions. 

• Experience designing and delivering AI systems in production environments. 

• Excellent communication skills and the ability to influence beyond your immediate team. 

• Great mentoring skills. 
• Comfort working across multiple projects and shifting priorities. 

Nice to Have 

• Experience with observability and evaluation tools such as LangFuse, Weights & Biases, or similar. 

• Familiarity with agentic evals and prompt‑engineering patterns. 

• Background in consulting, technical advisory, or cross‑functional leadership roles. 

• Experience with cloud platforms (AWS, GCP, Azure) and modern MLOps practices. 

Why we're hiring:

We are looking for a Data Analyst to support in the continued development of WPP’s client operations analytics team, using business intelligence tools and visualisations to share with WPP HQ and the wider WPP network.

What you'll be doing:

Reporting into the Director of Data Operations, this role will work in several capacities including analysing data, creating technical solutions, assessing business issues, rolling out a software solution and building internal client relationships. In this role you will help to bring insights directly to the business, enabling senior stakeholders to make informed data driven decisions on a daily basis.

The role will be as follows:

• Support our ETL (Extract, Transform & Load) process for all current & future data feeds
• Work with all existing agencies data feeds to identify & resolve any validation concerns
• Create and/or manage WPP’s master data tables
• Assist with new agency/country implementation programmes
• Filter and “clean” data by reviewing validation reports and performance indicators to locate and correct code & data process problems
• Provide ad hoc analysis to key client stakeholders

Who you'll be working with:

You’ll be working closely with all of the Data & Insights team which currently consists of 13 people (8 based in UK, 2 based in Madrid & 3 based in India) who are nice group of individuals and are a close working team that all get on well, and who are looking forward to what this team could achieve in the future.

You will also be working closely with the Data Manager, EVP of Marketing & Growth Operations, other stakeholders from WPP Operating Companies.

We've adopted a hybrid working approach to give more flexibility on where and how we work. Normally we work together in our amazing office twice a week.

This role reports to the Director of Data Operations within the Enterprise Data Group team.

What you'll need:

• Strong analytical and problem-solving skills
• Proficiency in SQL and Python (pandas, PySpark) for data analysis
• Hands-on experience with Databricks or a comparable cloud platform (Snowflake, BigQuery)
• Familiarity with modern data formats (CSV, JSON, Parquet, Delta)
• Attention to detail and a willingness to learn new tools
• Fundamental understanding of REST APIs is desirable, but not mandatory
• Exposure to AI-assisted analytics workflows (e.g. Claude, Copilot, Genie) is a plus

Who you are:

You're open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.

You're optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected.

You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.

What we'll give you:

Passionate, inspired people – We aim to create a culture in which people can do extraordinary work.

Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry.

Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge?

#LI-Hybrid 

Why we're hiring:

As a Data Engineer in the WPP Enterprise Data Group, you will be responsible for the design and implementation of scalable data solutions providing enterprise-scale data transformation across a broad range of projects.
Your role will focus on delivering solutions that utilize large-scale data ingestion, processing, storage/querying, streaming, and batch analytics using Databricks. As part of a team, you will implement world-class solutions designed by our data architects. Your responsibilities will include estimating, designing, coding, testing, deploying, and ensuring scalability and performance on Azure using key technologies like Databricks.
As a hands-on technologist with an extensive data engineering background using Databricks, you will be joining a group of Data Engineers who are passionate about building the best possible solutions for our business and endorse a culture of life-long learning and collaboration.

What you'll be doing:

• Design, build, test and maintain data pipelines (ELT), according to business and technical requirements.
• Implement secure platforms with data governance in mind.
• Play a key role in automation and building industry leading solutions against architectural best practices.
• Propose technical designs and develop integrations.
• Deliver data migrations between legacy & modern platforms
• Design & deliver data warehousing solutions and key data engineering workstreams for any required solution.
• Support cross-functional teams across the data space.

What you'll need:

Minimum requirements for this role include:

• 3+ years of experience designing and building scalable distributed data pipelines and dimensional data models
• 3+ years of experience in Python and SQL
• Experience using Databricks platform and PySpark is a must.
• Extensive experience of Microsoft Azure data services – Data Factory, ADLS gen2, Event Hubs, Azure SQL, Azure Key Vault
• Ideally experience in the following – Kafka, Delta Lake, Pandas
• A demonstrable understanding of Continuous Integration, Continuous Delivery (CI/CD) and Agile practices, unit & integration tests and development practices using Azure DevOps.
• Fluency in English.
• Exposure to AI & ML technologies is a plus.

Who you are:

You're open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.

You're optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected.

You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.

What we'll give you:

Passionate, inspired people – We aim to create a culture in which people can do extraordinary work.

Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry.

Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge?

#LI-Hybrid 

Opportunity Overview:

We are seeking a Technical, Hands-on Manager to lead a team responsible for building and maintaining high-quality healthcare market datasets and analytics that power internal insights, benchmarking, and external thought leadership.

In this role, you will lead a team of data analysts responsible for the development, quality assurance, and ongoing refresh of market data assets. You will combine strong people leadership with technical expertise in analytics and data science to ensure reliable, scalable data pipelines and actionable insights.

The ideal candidate is both a strong people manager and a hands-on analytics leader who can guide analysts in rigorous data methodology, translate data outputs into meaningful business insights, and partner closely with commercial strategy, product, clinical, and analytics stakeholders.

What you’ll do:

• Lead and develop a team of data analysts responsible for the creation, validation, and ongoing refresh of healthcare market datasets.
• Mentor analysts in data methodology, statistical reasoning, and reproducible analytics practices to ensure consistent and rigorous analysis across the team.
• Establish analytic standards, coding practices, and documentation expectations to ensure all datasets and insights produced by the team are reproducible and scalable.
• Establish and maintain governance processes for market data including versioning, documentation, auditability, and traceability of data sources and methodologies.
• Oversee change-detection logic, ensuring the team systematically identifies and documents additions, removals, and shifts in the market dataset.
• Define and enforce data quality standards across ingestion, transformation, and analysis workflows.
• Collaborate with Data Engineering and Platform teams to ensure the underlying data infrastructure supports scalable ingestion, transformation, and analytics workflows used by the analyst team.
• Translate analytic outputs into business insights, benchmarks, and structured datasets that support product strategy, commercial enablement, and thought leadership initiatives.
• Drive the implementation of project scope definition, effort estimation, and planning in close coordination with cross-functional teams.
• Conduct code reviews and analytics methodology reviews to ensure maintainable, reproducible data workflows and high-quality analytic outputs.

What you’ll need:

Must-haves

• 7+ years of professional experience in data analytics, data science, or quantitative analysis in a production environment.
• Strong proficiency in Python and data analysis libraries (Pandas, NumPy, SciPy, Matplotlib).
• Advanced SQL querying and ability to work with large datasets.
• Strong understanding of statistics, data analysis methods, and pattern detection in complex datasets.
• Experience managing multiple concurrent analytics projects and prioritizing work across a team of analysts.
• Experience designing analytic frameworks or benchmark datasets used by business teams or external stakeholders.
• Experience managing data quality, data governance, and dataset lifecycle management.
• Experience evaluating and applying modern analytics or AI techniques (including LLM-based tools where appropriate) to enrich datasets or accelerate analytic workflows.
• Experiment and rapidly prototype design frameworks and validate hypotheses efficiently.
• Strong software engineering fundamentals including modular Python code, reusable analytic functions, and maintainable data pipelines.
• Familiarity with cloud data platforms (e.g., AWS, GCP, or Azure) and common data services used to store, process, and query large datasets.
• Work seamlessly across Data Science, Engineering, Product, DevOps, and Data Engineering teams to align technical decisions with business goals, ensuring smooth integration of AI/ML capabilities into production systems
• Excellent communication and storytelling skills, capable of translating complex AI/ML concepts into clear, actionable insights for leadership, stakeholders, and non-technical partners.
• Ownership mindset with end‑to‑end accountability, ensuring delivery from concept to deployment to monitoring—while continuously identifying risks, blockers, and opportunities for improvement.

Nice-to-haves

• Background in healthcare payment integrity, clinical data workflows, or payer/provider analytics.
• Thought leadership in analytics-driven market intelligence, benchmarking, or healthcare data insights.
• Experience working with healthcare claims, authorization, or utilization management data.
• Experience producing market intelligence, benchmarking studies, or industry datasets.
• Familiarity with healthcare payer workflows or healthcare analytics environments.
• Familiarity with compliance, governance, and security best practices for healthcare data (HIPAA, PHI handling, logging, auditing).

Ability to commute/relocate:

• Nacharam, Hyderabad, Telangana*: Reliably commute or planning to relocate before starting work (Preferred)

Interview Process*:

1. Connect with Talent Acquisition 
2. Meet with the Hiring Manager
3. Behavioral Interview(s)
4. Case Study
5. Interview with Senior Leadership

*Subject to change

About Cohere Health:

Cohere Health’s clinical intelligence platform delivers AI-powered solutions that streamline access to quality care by improving payer-provider collaboration, cost containment, and healthcare economics. Cohere Health works with over 660,000 providers and handles over 12 million prior authorization requests annually. Its responsible AI auto-approves up to 90% of requests for millions of health plan members.

With the acquisition of ZignaAI, we’ve further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate™, an AI-driven clinical and coding validation solution that operates in near real-time. By unifying pre-service authorization data with post-service claims validation, we’re creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures providers are paid promptly and accurately.

Cohere Health’s innovations continue to receive industry wide recognition. We’ve been named to the 2025 Inc. 5000 list and in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024. Backed by leading investors such as Deerfield Management, Define Ventures, Flare Capital Partners, Longitude Capital, and Polaris Partners, Cohere Health drives more transparent, streamlined healthcare processes, helping patients receive faster, more appropriate care and higher-quality outcomes.

The Coherenauts, as we call ourselves, who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone.

We can’t wait to learn more about you and meet you at Cohere Health!

Equal Opportunity Statement: 

Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all.  To us, it’s personal.

Okta seeks a skilled NetSuite Developer to optimize, customize, and maintain our NetSuite ERP system. As part of our Business Technology team, you will be responsible for developing scripts, workflows, integrations, and system enhancements to improve business processes and scalability. This role will report to the Manager in Bangalore, India. We would love to hear from you!

Job Duties and Responsibilities

• Design and implement custom Generative AI solutions using the SuiteScript Generative AI API for practical NetSuite use cases
• Develop and maintain robust off-platform integration scripts, utilizing Python & LangChain and to manage data transfer and interaction between NetSuite (via SuiteTalk or RESTlets) and external AI/ML platforms, particularly for data preprocessing before RAG operations.1..
• Closely work with the BT team to design, develop, test, implement & support system solutions primarily in Finance Technology.
• Provide technical consultant, best practices, and problem resolution.
• Support & resolve production issues
• Develop and maintain integrations with third-party applications via REST/SOAP APIs

Required Skills:

• 9+ years in Python and its libraries (e.g., Pandas, Boto3) for data manipulation, ETL processes, and developing serverless functions to interact with foundational AI services on platforms like AWS Bedrock.
• Proficiency in NetSuite development experience (SuiteScript, SuiteFlow, SuiteTalk).
• Experience with SuiteCloud tools, REST/SOAP APIs, and third-party integrations.
• Experience with the SuiteScript Generative AI APIs to integrate LLM capabilities for advanced scripting solutions.
• Strong understanding of NetSuite ERP modules (Order Management, Billing, Vendor bill, etc.).
• Proficiency in JavaScript, SQL, and related web technologies
• Configure NetSuite modules to align with business needs, including leveraging Prompt Studio to customize and manage NetSuite AI functions like Text Enhance.
• Ability to drive and architect solutions with other developers, focusing on maximizing the value of embedded NetSuite AI capabilities.
• Deep practical experience in Prompt Engineering and iterative refinement of prompts within NetSuite Prompt Studio to maximize the relevance and accuracy of NetSuite AI outputs like Text Enhance.1
• Familiarity with containerization and orchestration tools (e.g., Docker) for deploying Python-based external services that augment NetSuite's capabilities
• Experience with ERP like Oracle Fusion Cloud Applications or SAP H4/HANA is a plus.
• Nice to have some experience with foundational AI services, including the desire to utilize a unified platform like AWS Bedrock for Generative AI development and deployment

Education and Certifications

• A Bachelor’s degree in Computer Science or Information Systems or equivalent years of industry experience
• NetSuite Administration or ERP consultant certification is an advantage

#P22115_3060755
#LI_Hybrid_Bengaluru

Okta seeks a skilled Staff Full Stack Engineer with expertise in NetSuite and/or  Oracle Fusion Cloud Applications. As part of our Business Technology team, you will be responsible for developing and optimizing full-stack solutions, including custom scripts, workflows, integrations, and system enhancements for both NetSuite and Oracle Fusion to improve business processes and scalability. This role will report to the Manager in Bangalore, India. We’d love to hear from you!

Job Duties and Responsibilities

• Design, develop, and maintain full-stack solutions for Finance Tech stack like NetSuite, Coupa and Oracle Fusion Cloud Applications etc., using any of the full-stack applications like Node Js/React
• Develop and maintain robust off-platform integration scripts using Python & LangChain to manage data transfer and interactions between NetSuite (via SuiteTalk or RESTlets) and AI Platforms
• Architect and implement scalable, secure, and cost-efficient cloud-native solutions on AWS for RAG, MCP, and Agentic AI (LangGraph) 
• Closely work with the BT Product Manager to design, develop, test, implement & support system solutions primarily in Finance Technology
• Provide technical consultation, best practices, and problem resolution for AI and Agentic AI for the Finance tech stack NetSuite, Oracle Fusion, and associated integrated systems
• Support & resolve production issues across the full application stack
• Develop and maintain integrations with third-party applications via REST/SOAP APIs
• Design and implement custom Generative AI solutions using the SuiteScript Generative AI API for practical NetSuite use cases and explore similar capabilities in Oracle Fusion

Required Skills:

• 9+ years in Python and its libraries (e.g., Pandas, Boto3) for data manipulation, ETL processes, and developing serverless functions to interact with foundational AI services on platforms like AWS Bedrock.
• Deep hands-on experience with AWS solutioning, including designing and deploying production applications using core services such as AWS EC2, AWS Lambda, Amazon S3, Amazon RDS, and API Gateway. Familiarity with Infrastructure as Code (IaC) tools like CloudFormation or Terraform is essential.
• Proficiency in NetSuite development experience (SuiteScript, SuiteFlow, SuiteTalk).
• Experience with SuiteCloud tools, REST/SOAP APIs, and third-party integrations.
• Experience with the SuiteScript Generative AI APIs to integrate LLM capabilities for advanced scripting solutions
• Strong understanding of Finance Business processes (Order Management, Billing, Vendor bill, etc.).
• Proficiency in JavaScript, SQL, and related web technologies
• Configure NetSuite modules to align with business needs, including leveraging Prompt Studio to customize and manage NetSuite AI functions like Text Enhance.
• Ability to drive and architect solutions with other developers, focusing on maximizing the value of embedded NetSuite AI capabilities
• Working Experience on the MCP and familiar with SaaS MCP connectors, like NetSuite MCP or similar
• Working experience with foundational AI services, with a desire to use a unified platform like AWS Bedrock for Generative AI development and deployment
• Nice to have some core Amazon Machine Learning (ML) services, specifically AWS SageMaker (for building, training, and deploying custom ML models), AWS Comprehend (for natural language processing and text analytics), and  Retrieval Augmented Generation (RAG)

Education and Certifications

• A Bachelor’s degree in Computer Science, Information Systems, or equivalent years of industry experience
• AWS cloud Certification or any ERP foundation certificate is a plus

#P25153_3431422
#Linkedin_Hybrid

The Opportunity:

Are you a data-driven storyteller with a passion for transforming raw information into actionable insights that drive tangible business outcomes? Do you thrive on collaborating directly with business stakeholders to understand their needs and then architecting elegant data solutions? If so, we have an exciting opportunity for a highly skilled and motivated Manager-level Business Analytics to join our growing team in Bangalore. In this role, you will be instrumental in empowering our business users with the data and visualizations they need to make informed decisions, analyze and drive improvements to our Finance operational performance, business decisions, and strategy. You will drive the analytics lifecycle, from initial consultation to the delivery of impactful dashboards and data sets.

What You'll Do:

• Strategic Alignment: Drive cross-functional alignment and prioritization of Finance analytics initiatives to generate actionable insights and tangible business improvements.
• Become a Trusted Advisor: Partner closely with business users across various departments to understand their strategic objectives, identify their analytical requirements, and translate those needs into clear and actionable data and reporting solutions.
• Consultative Analysis: Engage with stakeholders to explore their business questions, guide them on appropriate analytical approaches, and help them define key metrics and performance indicators (KPIs).
• Data Architecture & Design: Partner with our Data and Insights team to design and develop robust and efficient data models and datasets optimized for visualization and analysis, ensuring data accuracy and integrity.
• Enterprise Partnership & Analytics Foundations: Partner with the Enterprise Data & Insights team to align Finance with company-wide data standards and policies while developing the foundational infrastructure and capabilities of the Finance Analytics function.
• Expert Tableau Development: Leverage your deep expertise in Tableau to create intuitive, interactive, and visually compelling dashboards and reports that effectively communicate key insights and trends. Establish visualization best practices and storying and enable Finance report builders to adopt them.
• Data Wrangling & Transformation: Utilize Fivetran and/or Python scripting to extract, transform, and load data from various sources into our analytics platforms.
• End-to-End Ownership: Take full ownership of the analytics projects you lead, from initial scoping and data acquisition to dashboard deployment, user training, and ongoing maintenance.
• Drive Data Literacy: Educate and empower business users to effectively utilize dashboards and data insights to drive business outcomes.
• Stay Ahead of the Curve: Continuously explore new data visualization techniques, analytical methodologies, data technologies, and AI capabilities for interactive analytics to enhance our analytics capabilities.
• Collaborate and Communicate: Effectively communicate complex analytical findings and recommendations to stakeholders. Lead cross-functional collaborations to achieve project goals.
• Data Governance & Quality: Champion data accuracy, consistency, and integrity across Finance, driving robust governance and maintaining core foundations such as the reporting inventory, structure, access, and data dictionary.
• Performance Monitoring & Iteration: Monitor the performance and user adoption of developed dashboards, gather feedback, and implement necessary revisions for continuous improvement.
• Documentation & Training: Develop comprehensive documentation for created dashboards and datasets. Provide training and support to business users to ensure effective utilization of analytics tools.

What You'll Bring:

• 8+ years of experience in a Business Analytics, Data Analytics, or similar role with increasing responsibility.
• Proven experience working directly with business stakeholders to understand their needs and deliver data-driven solutions.
• Expert-level proficiency in Tableau, including advanced calculations, parameters, actions, and performance optimization.
• Strong hands-on experience in building and optimizing data sets for Tableau.
• Solid experience with data integration tools, preferably Fivetran, and the ability to design and implement data pipelines.
• Proficiency in Python for data manipulation, cleaning, and transformation (e.g., using libraries like Pandas).
• Strong understanding of data warehousing principles and experience with platforms such as Snowflake or Redshift.
• Advanced SQL skills for data extraction, transformation, and querying.
• AI literate, experience with traditional and generative AI. 
• Excellent problem-solving and analytical skills with a strong attention to detail and the ability to translate business questions into analytical frameworks.
• Exceptional written and verbal communication skills, with the ability to present complex data insights effectively to both technical and non-technical audiences.
• Proven ability to manage multiple analytics projects simultaneously, prioritize tasks, and meet deadlines effectively.
• Excellent collaboration and interpersonal skills with the ability to build strong working relationships with business stakeholders.
• Bachelor's degree in a quantitative field such as Engineering, Finance/Accounting/ Business, Economics, Statistics, Mathematics, Computer Science, or a related discipline. (Master's degree a plus).

Bonus Points For:

• Experience in SaaS software industry is highly preferred.
• Experience with other data visualization tools (e.g., Power BI, Looker).
• Familiarity with cloud-based data platforms (e.g., BigQuery).
• Familiarity with basic statistical concepts and methodologies is a plus.

This role is hybrid, with the expectation of working from our local office on specified days based on local expectations. We will continuously assess this arrangement, and it may be subject to change based on business needs and evolving circumstances.

#LI-Hybrid

P22262_3137714

The Role

Lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

The Role

The Senior Data Scientist will lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

Rhombus Power India is purposefully transforming the nation’s defense and national security enterprises with Guardian, its Artificial Intelligence platform for strategic, operational, and tactical decision-making at the speed of relevance.

We are looking for people who are driven by a sense of purpose. In this role, you will serve as a Data Engineer to solve our customer’s uniquely complex problems. We expect you to be a systems-level thinker and a real doer. You will excel in this role if you are hungry to make a difference and are intellectually bold. And we sure hope that you smile when you hear our clients say, “If we can dream it, Rhombus can do it.”

Come join our cross-disciplinary and world-class team of technologists who are working hard every day to deliver game-changing solutions to transform national security.

Location

New Delhi, India

Job Description

Rhombus’ Data Engineers are instrumental in designing and implementing data engineering activities on topical, mission-driven projects that inform our national security agenda. They analyze, build, and maintain our organization’s data infrastructure and processing systems. As a Data Engineer, you’ll perform various code development and query needs for integration with new and existing applications, dashboards and machine learning pipelines. You’ll work cross functionally with other departments and utilize your skills at all stages of the analytics pipeline to create results that drive business values and customer success! You’ll be asked to travel to client sites where you’ll engage and collaborate directly with the client to discuss data pipelines, solutioning, and to ensure a strong client connection.

Responsibilities:

• Develop code using various programming and scripting languages to automate data ingestion and improve data management processes.
• Architect data repositories, stand up data platforms and develop data pipelines for ingestion, transformation, and aggregation.
• Review existing architecture, data strategy, and improve processes for data governance, data quality, and metadata management.
• Extract and analyze raw data from multiple data sources via APIs, SQL Stored Procedures, or Python scripts.
• Ability to develop scripts and programs for converting various types of data into usable formats and support project team to scale, monitor and operate data platforms.
• Collaborate with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced, agile environment.
• You’ll use your experience in analytical exploration and data examination while you manage the assessment, design, building, and maintenance of scalable platforms for clients.
• Communicate project status and results to various levels of leadership.

Qualifications:

• A Bachelor’s degree in Data Analytics, Computer Science, Computer Engineering, Information Systems/Sciences, or other relevant area (or equivalent experience) and at least 1 year of professional experience, or a Master’s degree with strong academic project experience.
• Experience with 1 or more programming and scripting languages, with a strong focus on Python, Pandas and Numpy. Other languages include: Shell, PERL, Java, C/C++/C#, Scala, etc.
• Experience with 1 or more of the following relational, noSQL and/or file based storage (e.g. MYSQL, MongoDB, SQL Server, Oracle, Postgres, Hbase, DynamoDB, etc.)
• Experience building and maintaining ETL data pipelines
• Experience with software development life cycle including testing, documenting, delivery and support
• Working knowledge of AWS/cloud technologies
• Experience using query optimization as well as data modeling techniques.
• Familiarity with machine learning frameworks (such as TensorFlow, Scikit-Learn, etc.)

Personal Qualities:

• Ability to contextualize data as it relates to Rhombus’ vision. We want someone who can understand the “why” and “so what”, and not just the “how”. Our Data Engineers help us transmit the enthusiasm we have around the data work to the individuals doing that work.
• Must have strong problem-solving skills and demonstrated excellent oral and written communication skills.
• We’re seeking folks with strong intellectual curiosity and creativity, with an ability and willingness to learn new skills and apply novel solutions to problems.
• Comfort in a fast-paced start-up environment is crucial, with the ability to consistently revise your approach in response to new information, and to be flexible and adaptive.

About HG Insights

HG Insights is the pioneer of Revenue Growth Intelligence. For more than a decade, we have delivered comprehensive, AI-driven datasets on B2B buyers, technology adoption, IT spend, and buyer intent, sourced from billions of data points. Today, we are a trusted partner to Fortune 500 technology companies, hyperscalers, and innovative B2B vendors seeking precise go-to-market analytics and decision-making.

Through an evolving suite of AI agents that incorporate first-party data and buyer signals, HG Insights enables AI-powered GTM automation across sales, marketing, RevOps, and data analytics teams, modernizing GTM execution from strategy through activation.

Role Overview

The Applied Data Scientist - Research is a collaborative analytical partner to the Head of Data Science, contributing to the design and validation of GTM insights that power the Contextual Intelligence initiative.

You will co-develop insight logic, selecting signals, designing scoring frameworks, prototyping models in Python, and validating outputs. You will also contribute to the production-ready briefs that are implemented in the data production pipeline by the engineering team.

This role sits at the intersection of statistical modeling, structured data analysis, and applied AI. You are comfortable reasoning about how to measure something rigorously, how entities and relationships in a knowledge graph can be leveraged, and how to use LLMs as a practical tool in the insight development workflow, not as a subject of research, but as part of the toolkit.

What You Will Do

Insight & Model Development

• Co-develop scoring frameworks and metrics models, contributing to signal selection, weighting logic, and model structure across a range of GTM insight types (acquisition,expansion, retention, strategic)
• Prototype insight logic in Python notebooks: assembling features from HG's structured data assets, implementing model components, and stress-testing outputs.
• Design and run validation experiments to confirm that insight outputs are directionally correct, well-calibrated, and meaningful across the full vendor universe
• Contribute to ontology and entity design, thinking through how vendors, products, companies, and relationships should be structured to support a given insight, informed by a conceptual understanding of the knowledge graph schema

Production Brief Development

• Translate insight designs into clear, implementation-ready production briefs 
• Document model specifications precisely: component definitions, feature engineering, aggregation logic, edge case handling, and expected output distributions
• Participate in handoff reviews with the production function, answering implementation questions and refining specs based on feasibility feedback

Insight Research & Discovery

• Contribute to the prioritized insights catalog, researching new insight ideas, assessing data availability, and framing feasibility
• Stay current on GTM data science approaches, competitive intelligence methodologies, and relevant analytical techniques that could expand the insight library

What We're Looking For

Core Skills

• Statistical modeling depth: Ability to design and implement a range of scoring and metrics models from first principles; comfortable with component weighting, normalization, signed rate-of-change metrics, composite aggregation, and distribution analysis; knows when a technique is appropriate and why 
• Python for analytical prototyping: Strong notebook-based Python for data manipulation, feature construction, model prototyping, and output validation; pandas, NumPy, and Scikit are daily 
• SQL: Proficient in querying structured data at scale; used for signal extraction, feature derivation, and validation checks across large vendor and company datasets
• Analytical rigor & validation thinking: Ability to critically evaluate whether a model is measuring what it claims to measure; designs validation experiments, checks edge cases, and flags when outputs don't pass a sanity check
• Clear technical communication: Able to translate analytical logic into precise written specifications; the production brief is a key deliverable 

Applied AI & Graph Literacy

• LLM API usage: Hands-on experience using Claude, GPT, or equivalent APIs as a practical tool; can design effective prompts, integrate LLM steps into an analytical workflow, and evaluate output quality critically
• Knowledge graph concepts: Conceptual understanding of how entities, relationships, and properties are structured in a graph; able to reason about how graph-derived features (e.g., vendor-product-company traversals) should inform insight design, without necessarily writing production Cypher 

Nice to Have

• GTM/Management Consulting, or IT Research experience, familiarity with concepts like install base, intent signals, competitive intelligence, and market analysis. Experience writing Cypher or querying graph-structured data directly
• Experience working collaboratively with engineering, product and GTM teams
• Experience in a B2B SaaS or data products environment

Tools & Environment

Primary

• Python (pandas, NumPy, scipy, Jupyter)
• SQL
• LLM APIs (Claude, GPT)
• Git and version control

Working Knowledge

• Databricks
• Cloud storage 
• Knowledge graph concepts 

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…..

Role Description

• As a Senior Applied Value Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

Key Responsibilities:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Senior Applied Value Engineer stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Senior Applied Value Engineer specialize in domains (e.g. supply chain) and industries

Requirements:

• 6+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

Company Overview

At CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world’s most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics.

We are in hyper growth mode, having recently raised our Series D funding at unicorn valuation (>$1B) and ended our third year of triple-digit revenue growth. Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail ecommerce platforms, and delivering exceptional customer service to unlock high net retention rates.

What You’ll Be Doing

As a Lead ML Engineer in the Data Science team, you will work closely with the engineering, product, and operations teams to build state-of- the-art ML based solutions for B2B SaaS products. This will entail applying advanced ML algorithms at scale for core products and developing robust end to end production pipelines which includes Human-in-the-Loop component to boost the quality. 

In this role, you will find innovative ways to apply emerging technologies to improve business processes and drive more value for customers. The ideal candidate will have a strong background in machine learning model development, natural language processing and understanding, and data analysis which they can utilize to manage and improve our company’s AI/ML initiatives. 

• Architect and Own multiple AI driven end to end pipelines that allows for deployment and scalability of machine learning models
• Build tools and capabilities that help with data ingestion to feature engineering, data management and organization
• Build tools and capabilities for scalability through distributed optimization 
• Deploy  cutting edge algorithms like LLMs etc. on GPUs at scale
• Work with stakeholders on the research and software engineering side of the company to understand how to support their teams
• Build tools and capabilities for model management and model performance monitoring
• Build operating services at scale with high availability and reliability
• Propose and implement the best engineering practices for scaling ML-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features
• Contribute and influence the ML infrastructure roadmap in collaboration with Data Science team

What we are looking for -

• Bachelor’s or Masters in Computer Science or Maths/Stats from a reputed college with 5+ years of experience in solving of experience in machine learning engineering problems 
• Experience and understanding of the entire machine learning pipeline from data ingestion to production
• Experience with machine learning operations, software engineering, and architecture
• Experience with large-scale systems including parallel computing and GPUs
• Experience architecting and building an AI pipelines that supports productionization of ML models
• Experience with MLOps systems
• Strong programming skills in a scientific computing language such as Python, SQL
• Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy
• Experience working with ML tools such as Tensorflow, Keras, and Pytorch
• Ability to take successful, complex research ideas from experimentation to production
• Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
• Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra

Why you will love to work with us -

We have multiple brands, which are among the biggest brands operating on amazon, as our customers. You will be responsible for working with their data and developing models and algorithms to drive lift in tune of hundreds of thousands of dollars.

• Opportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models
• Deploy code using the most sophisticated tech stack like AWS, GCP etc.
• You will own projects end to end i.e., from exploration to final production
• You will be empowered to make decisions. It implies more responsibilities but high learning
• Immense opportunities to learn and develop ML based SaaS products for brands and get company-wide recognition
• Forget endless meetings. Get things done and start making an impact from day 1
• Work hard, have amazing fun, create history, build the future of eCommerce 
• Start-up environment with a strong culture and values to accelerate your career 

Role Description

• As a Senior Applied Value Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

Key Responsibilities:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Senior Applied Value Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

• 6+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

The Team:

The Celonis Value Engineering (VE) team is focused on managing the entire customer value lifecycle, from sales through value realization, renewal and expansion. As a Value Engineer - India, your primary focus will be supporting our GCC's (Global Competency Centers) across the Adopt and Expand phases of our customer value journey. This team will be a part of the Global VE CoE spearheading our mission of data-driven business transformation with our customers.You will blend deep process and industry expertise with a proven consulting skill set with strong analytical skills at the forefront of one of the fastest-growing tech companies worldwide.

The Role:

As an Applied AI Value Engineer you are pushing the envelope in solving mission-critical problems for our customers. You will be working with our most strategic customers, understanding their strategy and key challenges, and building Celonis solutions using cutting edge AI technologies of market leaders such as Microsoft and OpenAI. With Celonis’ market leading Process Intelligence (PI) Platform we feed operational context to AI so it understands our customers’ businesses and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

The work you’ll do:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Applied AI Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

The qualifications you need:

Requirements:

• 4+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

Role Summary

We are looking for a technically strong AI / ML Developer with hands-on expertise in training and fine-tuning Small Language Models (SLMs) and RAG Solutions. The ideal candidate will drive end-to-end AI Solutions — from dataset curation and pre-processing to training, evaluation, and production deployment. You will collaborate closely with product, product engineers, and infrastructure teams to build AI solutions that are efficient, scalable, and business-aligned.

Key Responsibilities

1  Model Design & Training

• Design, train, and fine-tune Small Language Models (SLMs) using frameworks such as PyTorch, TensorFlow, or JAX.
• Conduct experiments with supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning.
• Implement efficient training pipelines leveraging distributed training (DDP, FSDP) across GPU/TPU clusters.
• Perform hyperparameter optimisation, ablation studies, and model selection based on benchmark results.
• Develop and maintain data pipelines for collecting, cleaning, tokenising, and pre-processing large-scale training corpora.

2  Model Evaluation & Quality

• Define and implement evaluation frameworks including perplexity, BLEU, ROUGE, BERTScore, and task-specific benchmarks.
• Conduct red-teaming, bias analysis, and safety evaluations to ensure responsible AI deployment.
• Benchmark models against established baselines (e.g., GPT-2, Phi, Mistral) and track performance over iterations.
• Collaborate with QA teams to build regression suites for model versioning and continuous evaluation.

3  MLOps & Deployment

• Containerise and deploy models using Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker / GCP Vertex AI / Azure ML).
• Build and maintain model registries, experiment tracking (MLflow, Comet), and reproducible training pipelines.
• Optimise inference performance through quantisation (INT8, INT4), pruning, distillation, and ONNX/TensorRT conversion.
• Monitor model drift, data drift, and performance degradation in production; implement automated retraining triggers.

4  Research & Innovation

• Stay current with state-of-the-art NLP/LLM research; prototype and validate new techniques from published literature.
• Contribute to internal knowledge sharing, technical documentation, and model cards.
• Explore parameter-efficient fine-tuning (PEFT) methods such as LoRA, QLoRA, and Adapter layers.
• Investigate and apply mixture-of-experts (MoE), retrieval-augmented generation (RAG), and agentic workflows as needed.

5  Collaboration & Stakeholder Management

• Work with product managers and domain experts to translate business requirements into model objectives and KPIs.
• Communicate model capabilities, limitations, and trade-offs clearly to both technical and non-technical stakeholders.
• Participate in architecture reviews, sprint planning, and cross-functional design discussions.

Required Qualifications

1  Education

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related quantitative field.
• Equivalent professional experience with a strong portfolio of delivered AI/ML projects will be considered.

2  Experience

• 4 – 6 years of professional experience in machine learning or NLP engineering.
• Minimum 2 years of direct, hands-on experience in training or fine-tuning language models (LLMs or SLMs).
• Demonstrable experience taking a model from dataset preparation through to production deployment.

3  Technical Skills — Core

• Programming: Python (proficient); familiarity with C++/CUDA a plus.
• Deep Learning Frameworks: PyTorch (primary), TensorFlow or JAX.
• NLP Libraries: Hugging Face Transformers, Datasets, PEFT, TRL, Accelerate.
• Training Infrastructure: Multi-GPU training, FSDP, DeepSpeed ZeRO stages 1–3.
• Data Engineering: Pandas, NumPy, Apache Spark or Dask for large-scale data prep.
• Vector DBs & Retrieval: FAISS, Pinecone, Weaviate, or equivalent.
• Cloud Platforms: AWS, GCP, or Azure — ML-specific services (SageMaker, Vertex AI, etc.).
• Version Control & CI/CD: Git, GitHub/GitLab, MLflow or W&B for experiment tracking.

4  Technical Skills — Nice to Have

• Experience with multimodal models or vision-language models (VLMs).
• Knowledge of model safety, alignment techniques, and responsible AI frameworks.
• Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
• Contributions to open-source ML projects or publications at NeurIPS, ICML, EMNLP, ACL.

Behavioural Competencies

• Intellectual Curiosity: Keeps up with rapidly evolving AI research and applies learnings pragmatically.
• Problem Solving: Approaches ambiguous problems with structured, data-driven thinking.
• Ownership: Takes full accountability for model quality, timelines, and production reliability.
• Collaboration: Works effectively in cross-functional teams with diverse skill sets.
• Communication: Distils complex technical concepts for diverse audiences.
• Adaptability: Thrives in a fast-paced environment where priorities evolve with research breakthroughs.

The Role:

As an Applied Value Engineer for the Japan Market, you will solve business-critical problems for our most strategic Japanese customers. You will bridge the gap between cutting-edge AI technology and the unique business requirements of Japanese enterprises.
Working with the world’s leading Process Intelligence (PI) platform and partners like Microsoft, OpenAI, and Databricks, you will feed operational context to AI to help Japanese organizations industrialize AI and unlock real ROI. You will prototype solutions, demonstrate value to executives, and ensure successful implementation and adoption within the Japanese business ecosystem

The work you’ll do:

• AI Discovery & Solutioning (Japan Focus): Understand the specific AI strategies and challenges of Japanese customers. Translate their requirements into innovative solutions that align with local business practices.
• Hackathons & Prototyping: Rapidly build creative prototypes (LLM/Agent-based) to solve business-critical problems during customer hackathons.
• Agentic Process Transformation: Enable a fundamental shift for our customers from traditional automation to autonomous AI agents empowered by the Celonis PI Platform.
• Proof Projects: Execute end-to-end Proof-of-Value (PoV) projects, including architecture, RAG, and guardrails, ensuring compliance with enterprise data and identity frameworks.
• Cross-Border Collaboration: Work closely with the Japan-based account teams and executives to ensure project outcomes reach agreed value and adoption thresholds.
• Domain Specialization: Specialize in domains (e.g., Supply Chain, Finance) to scale knowledge across the Japan and global organizations.

The qualifications you need:

• Market Alignment: Strong willingness and commitment to work specifically for the Japan market. This includes flexibility to align with Japan Standard Time (JST) for key meetings and workshops.
• Professional Experience: 3-5 years of experience in technical pre-sales, defining AI roadmaps, and building ROI/TCO business cases.
• Technical Expertise: Deep understanding of Generative AI techniques (RAG, multi-agent orchestration, prompt engineering) and Python (LangChain, pandas, PyTorch, etc.).
• Process Knowledge: Understanding of business processes (Supply Chain, Finance, etc.) and the ability to translate high-level needs into AI use cases.
• Communication: Strong presentation skills to engage with both internal stakeholders and external Japanese enterprise executives.
• Education: Bachelor’s Degree required (Master’s in CS, Engineering, or Math preferred).

• Japan Market Experience: Previous experience working with Japanese companies as clients or partners is highly valued.
• Cultural Competency: Familiarity with Japanese business etiquette and communication styles.
• Hands-on AI implementation: Experience building agentic systems and deploying models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).
• LLM Ecosystem: Working knowledge of LangChain, LlamaIndex, or other OSS packages.

We’re looking for Backend Engineers to lead the design and delivery of SaaS products that are powered by data, machine learning, and AI. 

You’ll be the senior technical owner for one or more product areas, working across , backend, systems, and cloud infrastructure to: 

• Ship high-quality data/ML/AI powered features end-to-end 

• Integrate data/ML/AI capabilities into real customer workflows 

• Raise the bar on design, reliability, performance, and engineering practices across the org 

This is a hands-on senior role: you’ll write code, review designs, mentor senior engineers, and collaborate closely with product, design, data, and ML teams. 

What You’ll Do 

• Own the architecture and technical direction for key product areas in a multi-tenant SaaS platform. 

• Work with product, design, and data/ML teams to translate business problems into simple, robust technical solutions. 

• Drive the evolution of our system architecture (APIs, services, data flows, auth, tenancy, integrations) as the product and customer base scale. 

End-to-End Full-Stack Product Delivery 

• Build and maintain backend services and APIs (REST/GraphQL/gRPC) that power those experiences. 

• Deliver backend features end-to-end including data schemas and business logic. 

• Collaborate with UX and product to ensure responsive and delightful product experiences. 

Data / ML / AI Integration 

• Partner with data scientists and MLOps / platform teams to embed data, ML and AI capabilities into the product (recommendations, categorization, automation, routing, insights, LLM-powered workflows, etc.). 

• Design APIs, data contracts, and UX flows that make ML/AI features reliable, understandable, and safe for customers. 

• Ensure telemetry and feedback loops are in place so data/ML teams can measure performance, iterate models, and improve outcomes. 

• Help define and implement guardrails for AI features (fallbacks, explanations, error handling, permissions). 

Operational Excellence 

• Champion operability: monitoring, alerting, logging, and runbooks for services you own. 

• Lead efforts to improve performance, scalability, and resilience of critical paths (e.g., onboarding, reporting, AI-assisted workflows). 

• Work with security and compliance to ensure features meet requirements around authentication, authorization, data privacy, and multi-tenancy. 

• Participate in and help evolve on-call / incident response processes as a technical leader. 

Engineering Excellence & Leadership 

• Act as a technical mentor for multiple teams, raising the bar on code quality, reviews, testing, and design. 

• Lead technical design reviews and cross-team architecture discussions, especially where product, data, and ML intersect. 

• Help define engineering standards and best practices (API design, frontend patterns, error handling, observability, testing). 

• Partner with engineering management to shape roadmaps, staffing, and sequencing for major initiatives. 

What You’ll Bring 

Experience 

• 10+ years of software engineering experience 

• Demonstrated experience shipping data/ML/AI powered SaaS products, 

• Strong track record of owning and shipping complex, user-facing features end-to-end in collaboration with product management and UX. 

• Experience as a senior member of the technical staff in guiding teams and owning critical production systems. 

Technical Skills 

• Strong proficiency with at least one backend stack, for example: 

• Node.js/TypeScript, Java,  Go, Rust, or similar 

• Designing and building APIs, services, and integrations 

• Proficiency with Python and data analysis/modeling tools (e.g. pandas/pytorch) 

• Solid understanding of data modeling and storage: relational databases, caching, and basic data warehousing concepts. 

• Familiarity with data/ML/AI concepts: 

• How ML models or LLMs are exposed as services 

• Typical failure modes, latency/throughput considerations, and guardrails 

• Experience with cloud platforms (AWS / GCP / Azure), containers, and infrastructure (networking, scaling, security). 

• Strong habits around testing, CI/CD, code reviews, and incremental delivery. 

Mindset & Soft Skills 

• Product-minded engineer who cares about customer problems, usability, and outcomes, not just code. 

• Systems thinker who can balance short-term delivery with long-term architectural health. 

• Excellent communicator, comfortable driving alignment across engineering, product, data, and go-to-market teams. 

• Enjoys mentoring and multiplying the impact of other engineers. 

Senior Machine Learning Engineer

Location: (Bangalore or Noida) 

The proliferation of machine log data has the potential to give organizations unprecedented real-time visibility into their infrastructure and operations. With this opportunity comes tremendous technical challenges around ingesting, managing, and understanding high-volume streams of heterogeneous data

As a Machine Learning Engineer, you’ll build the intelligence behind the next generation of agentic AI systems that reason over massive, heterogeneous log data. You’ll combine machine learning, prompt engineering, and rigorous evaluation to create autonomous AI agents that help organizations understand and act on their data in real time.

You’ll be part of a small, high-impact team shaping how AI agents understand complex machine data. This is an opportunity to work on cutting-edge LLM infrastructure and contribute to defining best practices in context engineering and AI observability.

Responsibilities

• Design, implement, and optimize agentic AI components, including context engineering, memory management, and prompts.
• Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.
• Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes.
• Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement.
• Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience.

Required Qualifications

• B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field.
• 4-6 years of hands-on industry experience with demonstrable ownership and delivery.
• Strong understanding of machine learning fundamentals, data pipelines, and model evaluation.
• Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn); familiarity with JVM languages is a plus.
• Working knowledge of LLM core concepts, prompt design, and agentic design patterns.
• Strong communication skills and a passion for shaping emerging AI paradigms.

Desired Qualifications

• Prior experience building and deploying AI agents or LLM applications in production.
• Familiarity with modern agentic AI frameworks (e.g., LangGraph, LangChain, CrewAI).
• Experience with ML infrastructure and tooling (PyTorch, MLflow, Airflow, Docker, AWS).
• Exposure to LLM Ops - infrastructure optimization, observability, latency, and cost monitoring.

About Us

Sumo Logic, Inc. helps make the digital world secure, fast, and reliable by unifying critical security and operational data through its Intelligent Operations Platform. Built to address the increasing complexity of modern cybersecurity and cloud operations challenges, we empower digital teams to move from reaction to readiness—combining agentic AI-powered SIEM and log analytics into a single platform to detect, investigate, and resolve modern challenges. Customers around the world rely on Sumo Logic for trusted insights to protect against security threats, ensure reliability, and gain powerful insights into their digital environments. For more information, visit www.sumologic.com.

Sumo Logic Privacy Policy. Employees will be responsible for complying with applicable federal privacy laws and regulations, as well as organizational policies related to data protection.

Role Description

• As an Applied Value Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

Key Responsibilities:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Applied AI Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

• 5+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Experience in Oil & Gas industry is must.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

The below role is for our Bengaluru office. 

Director – Data Science 

Why Join Sigmoid? 

• Sigmoid provides the opportunity to push the boundaries of what is possible by seamlessly combining technical expertise and creativity to tackle intrinsically complex business problems and convert them into straight-forward data solutions. 
• Despite being continuously challenged, you are not alone. You will be part of a fast-paced diverse environment as a member of a high-performing team that works together to energize and inspire each other by challenging the status quo 
• Vibrant inclusive culture of mutual respect and fun through both work and play

Roles and Responsibilities: 

• Convert broad vision and concepts into a structured data science roadmap, and guide a  team to successfully execute on it. 
• Handling end-to-end client AI & analytics programs in a fluid environment. Your role will be a  combination of hands-on contribution, technical team management, and client interaction.
• Proven ability to discover solutions hidden in large datasets and to drive business results  with their data-based insights 
• Contribute to internal product development initiatives related to data science.
• Drive excellent project management required to deliver complex projects, including  effort/time estimation. 
• Be proactive, with full ownership of the engagement. Build scalable client engagement level  processes for faster turnaround & higher accuracy 
• Define Technology/ Strategy and Roadmap for client accounts, and guides implementation  of that strategy within projects 
• Manage the team-members, to ensure that the project plan is being adhered to over the  course of the project 
• Build a trusted advisor relationship with the IT management at clients and internal accounts  leadership. 

Mandated Skills: 

• A B-Tech/M-Tech/MBA from a top tier Institute preferably in a quantitative subject
• 15+ overall experience with 12+ years of hands-on experience in applied Machine Learning, AI and analytics
• Experience of scientific programming in scripting languages like Python, R, SQL, NoSQL, Spark with ML tools & Cloud Technology (AWS, Azure, GCP) 
• Experience in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scrapy, BERT etc.
• Strong grasp of depth and breadth of machine learning, deep learning, data mining, and statistical concepts and experience in developing models and solutions in these areas
• Expertise with client engagement, understanding complex problem statements, and offering solutions in the domains of Supply Chain, Manufacturing, CPG, Marketing etc. 

Desired Skills: 

• Deep understanding of ML algorithms for common use cases in both structured and  unstructured data ecosystems. 
• Comfortable with large scale data processing and distributed computing 
• Providing required inputs to sales, and pre-sales activities 
• A self-starter who can work well with minimal guidance
• Excellent written and verbal communication skills

WHO YOU ARE

You are a passionate Python and AI/ML Engineer minimum 4 years of hands-on experience building intelligent systems. You thrive in fast-paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting-edge Generative AI, scalable ML pipelines, and production-grade systems and you're energized by working at the frontier of what AI can do.

WHAT YOU'LL DO

1. Design, develop, and deploy machine learning models and Generative AI solutions — including classification, clustering, summarization, search & ranking, and information extraction.
2. Own end-to-end ML pipelines — from data ingestion and preprocessing through model training, deployment, and production monitoring.
3. Collaborate with cross-functional teams to translate business requirements into AI-driven features — applying NLP, outlier detection, and deep learning techniques where applicable.
4. Build robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments.
5. Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems.
6. Stay current with the latest advances in AI/ML — integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products.

WHAT YOU'LL NEED 

Python
Strong hands-on proficiency for building, scripting, and deploying AI/ML systems.
NumPy · Pandas · FastAPI · Scikit-learn
Machine Learning
Applied expertise across supervised, unsupervised, and deep learning — classification, clustering, outlier detection.
PyTorch · TensorFlow · XGBoost · DBSCAN

Generative AI (2+ yrs)
Hands-on experience building with LLMs — prompt engineering, RAG pipelines, summarization, and AI-powered features.
LLMs · RAG · Prompt Eng. · Fine-tuning

NLP & Search / Ranking
Processes language and builds relevance engines — NER, embeddings, semantic search, and ranking models.
spaCy · BERT · FAISS · Elasticsearch

API Development
Designs and ships secure, well-documented RESTful APIs exposing ML models as production-ready services.
REST · FastAPI · OAuth2 · Swagger

Databases
Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads.
PostgreSQL · MongoDB · Vector DBs

GOOD TO HAVE

Cloud Platforms
Deploys and scales AI workloads on AWS, Azure, or GCP.
AWS · Azure

TypeScript / JavaScript
Frontend or full-stack exposure for building ML-powered product interfaces.
TypeScript · React · Node.js

MLOps
Manages the ML lifecycle — tracking, versioning, and pipeline automation.
MLflow · Kubeflow · CI/CD

Containerization & Orchestration
Packages and scales AI services using containers and cluster management.
Docker · Kubernetes

About the Role

Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.

Key Responsibilities

• Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
• Develop and productionize ML models, taking them from prototype to scalable, live systems.
• Construct and manage the data pipelines required for model training, validation, and inference.
• Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
• Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
• Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
• Optimize applications for speed, scalability, and reliability.
• Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.

Required Qualifications

• Expert (10+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
• Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
• Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
• Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
• Data manipulation and analysis: Pandas, NumPy.
• Core ML frameworks: scikit-learn.
• Deep learning frameworks: Experience with TensorFlow or PyTorch.
• Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
• Experience with version control (Git) and CI/CD practices.
• Excellent problem-solving skills and the ability to write efficient, production-ready code.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
• Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
• Knowledge of large-scale data processing frameworks like Spark or Dask.

What Makes This Role Exciting

This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.

We are looking for a highly skilled and motivated Data and Analytics Systems Engineer to join our growing team. The ideal candidate will have a strong background in data engineering and analytics, with hands-on experience in designing, building, and maintaining data pipelines and analytics solutions. You will be responsible for leveraging a variety of technologies, including Google Cloud Platform, Google BigQuery, Tableau, Informatica, Databricks, Python, and Anaplan, to deliver high-quality data products and insights to our business stakeholders to ensure our Data & Analytics systems and operations are effective and efficient.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in a data engineering or analytics system management role.
• Proven experience with Google Cloud Platform (GCP), including Google BigQuery, Cloud Storage, and Cloud Functions.
• Experiences with data visualization tools, preferably Tableau.
• Proficiency in ETL/ELT tools like Informatica, Airflow, Dataproc, and so on.
• Experience with big data technologies such as Databricks and Spark.
• Strong programming skills in Python and experience with data manipulation libraries (e.g., Pandas, NumPy).
• Familiarity with the Anaplan platform is a plus.
• Excellent problem-solving and communication skills.
• Ability to work independently and as part of a team.

We are looking for a highly skilled and motivated Data and Analytics Systems Engineer to join our growing team. The ideal candidate will have a strong background in data engineering and analytics, with hands-on experience in designing, building, and maintaining data pipelines and analytics solutions. You will be responsible for leveraging a variety of technologies, including Google Cloud Platform, Google BigQuery, Tableau, Informatica, Databricks, Python, and Anaplan, to deliver high-quality data products and insights to our business stakeholders to ensure our Data & Analytics systems and operations are effective and efficient.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in a data engineering or analytics system management role.
• Proven experience with Google Cloud Platform (GCP), including Google BigQuery, Cloud Storage, and Cloud Functions.
• Experiences with data visualization tools, preferably Tableau.
• Proficiency in ETL/ELT tools like Informatica, Airflow, Dataproc, and so on.
• Experience with big data technologies such as Databricks and Spark.
• Strong programming skills in Python and experience with data manipulation libraries (e.g., Pandas, NumPy).
• Familiarity with the Anaplan platform is a plus.
• Excellent problem-solving and communication skills.
• Ability to work independently and as part of a team.

About the Role

Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.

Key Responsibilities

• Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
• Develop and productionize ML models, taking them from prototype to scalable, live systems.
• Construct and manage the data pipelines required for model training, validation, and inference.
• Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
• Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
• Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
• Optimize applications for speed, scalability, and reliability.
• Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.

Required Qualifications

• Expert (6+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
• Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
• Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
• Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
• Data manipulation and analysis: Pandas, NumPy.
• Core ML frameworks: scikit-learn.
• Deep learning frameworks: Experience with TensorFlow or PyTorch.
• Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
• Experience with version control (Git) and CI/CD practices.
• Excellent problem-solving skills and the ability to write efficient, production-ready code.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
• Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
• Knowledge of large-scale data processing frameworks like Spark or Dask.

What Makes This Role Exciting

This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.

About the Role

Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.

Key Responsibilities

• Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
• Develop and productionize ML models, taking them from prototype to scalable, live systems.
• Construct and manage the data pipelines required for model training, validation, and inference.
• Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
• Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
• Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
• Optimize applications for speed, scalability, and reliability.
• Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.

Required Qualifications

• Expert (6+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
• Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
• Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
• Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
• Data manipulation and analysis: Pandas, NumPy.
• Core ML frameworks: scikit-learn.
• Deep learning frameworks: Experience with TensorFlow or PyTorch.
• Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
• Experience with version control (Git) and CI/CD practices.
• Excellent problem-solving skills and the ability to write efficient, production-ready code.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
• Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
• Knowledge of large-scale data processing frameworks like Spark or Dask.

What Makes This Role Exciting

This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.

SLSQ127R200

As a Partner Solutions Architect (PSA) for India, you will work with the technical and sales team members who work directly with our customers. You will develop 'technical champions' within our top Partners, providing enablement on technical matters related to the Databricks product. Working with our partners, you will help our customers to achieve tangible data-driven outcomes through the use of our Databricks Lakehouse Platform, helping data teams complete projects and integrate our platform into their enterprise Ecosystem. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark™, MLflow, and Delta Lake; and major public cloud infrastructure and services. the product. You will use this expertise to become a trusted advisor to C&SI partners.

The impact you will have:

• Provide partners with the level of enablement they need to assist their clients in evaluating and adopting Databricks including hands-on Apache Spark™ programming and integration with the wider cloud ecosystem
• Engage with the partner technical community by leading workshops, seminars, and meet-ups
• You will be a Big Data Analytics expert on aspects of architecture and design and will share this with our partner network
• Show expertise by producing creative technical solutions and blog posts

What we look for:

• 8 years of customer facing experience working with external clients or partners across a variety of industry markets
• Core strength in either data engineering or data science
• Experience demonstrating technical concepts, including presenting and whiteboarding
• Experience developing architectures within a public cloud (AWS, Azure, or GCP)
• Hands on experience in SQL, Python, Scala, or Java
• Expertise in at least one of the following:
• Data Engineering technologies (Ex: Apache Spark™, Hadoop, Kafka)
• Data Warehousing (Ex: SQL, OLTP/OLAP/DSS)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, HPO)

Remote India

Hello👋I am Ashish, Product Operations Lead at Kayzen, and I am now looking for a Product Analyst  to join our team 🙌

But wait, you have not heard of Kayzen before?😃
Kayzen is a mobile demand-side platform (DSP) dedicated to democratizing programmatic advertising. We enable leading apps, agencies, media buyers, and brands to run programmatic customer acquisition, retargeting, and brand performance campaigns through its self-serve and managed service options.
Built on the three core pillars of performance, transparency, and control, Kayzen powers the world’s best mobile marketing teams with bespoke solutions that fuel business growth and deliver a competitive advantage. With an unprecedented scale of 160B+ daily ad requests from 1.6B+ unique users worldwide, we serve up to 1B+ ads per day in 180 countries. Kayzen is accessible through our APIs and user interface.

The team

The Product Analytics team sits at the intersection of data, product, business and engineering. We are a highly motivated group aligned in our quest to disrupt the multi-billion dollar ad-tech industry. You will collaborate with a carefully selected, diverse, and globally distributed team spanning customer success, engineering, data science, design, product and more.

Why This Role

As our Product Analyst, you will own the analytical layer that keeps our product honest and fast. You will pair deep product intuition with strong SQL skills and AI-accelerated workflows to diagnose issues, surface insights, and move faster than a traditional analyst role. This is not just about building dashboards — you will shape how we understand our product, automate recurring investigation work with LLM tools, and directly influence product and engineering decisions with data. If you love going deep on complex systems, debugging hard problems, and turning ambiguous data into clear action, this is your seat.

What You'll Do

Data Analysis & Insights

• Apply a broad range of analytical techniques to derive actionable insights from rich product and event data
• Work closely with the product team as a data-driven advisor and partner on strategic decisions and roadmap prioritisation
• Conduct deep-dive analyses on product performance, user behaviour, and funnel metrics to identify improvement opportunities
• Translate complex data findings into clear, concise narratives for technical and non-technical stakeholders

Product Support & Debugging

• Serve as the go-to person to analyse, debug, and resolve product issues in collaboration with engineering, Product and Business
• Go deep into complex customer-facing issues, identify root causes in data, and drive resolution with product and engineering teams
• Become a product and domain expert in RTB (Real-Time Bidding) and the broader programmatic advertising ecosystem

Automation & AI-Powered Workflows

• Leverage LLMs (GPT/Claude and similar tools) to automate recurring analyses, anomaly triage, data briefs, and BI request resolution — this is a mandatory part of how we work
• Build and maintain tools, scripts, and automated pipelines that reduce manual investigation effort and speed up response times
• Manage and resolve Business Intelligence requests; develop reusable tools to automate high-frequency reporting needs
• Contribute to internal dashboards and analytical tooling that accelerate decision-making across teams

Cross-Functional Collaboration

• Partner with engineering, data, customer success, and product teams on data-related initiatives and ad-hoc investigations
• Provide ideas and quantified feedback for product and process improvement
• Champion data quality, accuracy, and a culture of evidence-based decision-making across the organisation

Requirements

• 2+ years of AdTech industry experience in a data, analytics, or product analyst role
• Excellent SQL skills: comfortable writing complex queries including joins, CTEs, window functions, and aggregations against large datasets
• Hands-on experience with BI and data exploration tools (e.g. Redash, Looker, Metabase, or similar)
• Active user of AI tools (GPT, Claude, or similar) for analytical automation, data summarisation, and workflow acceleration. 
• Strong analytical and troubleshooting skills with a structured, hypothesis-driven approach to problem-solving
• High attention to detail and commitment to data accuracy and quality of output
• Ability to work collaboratively in a cross-functional, globally distributed team environment
• Self-starter mindset with goal-driven focus and resilience in a high-pressure, deadline-driven environment
• Passion for building great products and creating excellent experiences for customers

Nice to Have

• Python / pandas for ad-hoc analyses and light automation — not required, but a strong differentiator
• Familiarity with mobile attribution and measurement (AppsFlyer, Adjust, Singular)
• Familiarity with HTML/Rich media creatives

What do we offer?

• Exceptional career growth and learning opportunity
• A unique opportunity to be part of an experienced team of industry experts and entrepreneurs who bring massive change to the Adtech market
• Direct, day-to-day work experience with the management
• A fun, driven, and multinational team located across Germany, India, Argentina, Ukraine, Turkey, the UK and soon more countries
• A flexible work-from-home arrangement
• A 500-dollar home-office setup budget
• A 1000-dollar annual learning and development budget

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

1. 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).

1. Databricks

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

1. 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.

1. 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.

1. 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.

Job Description

We are looking for a Senior Data Scientist with a strong foundation in SQL/Python programming, data handling, and data wrangling to work on high-impact projects in the healthcare domain. This is a hands-on role involving advanced analytics, developing metrics and reports from large, complex datasets, and building scalable data solutions like solution workbenches.

The ideal candidate will demonstrate a strong aptitude for understanding business context, generating insights from data, and a proactive attitude toward learning and applying relevant data tools and techniques. A solid grasp of claims analytics, combined with the ability to work in the healthcare space and apply a wide range of quantitative and analytical methods to drive better business decisions, is essential. Experience or interest in Generative AI tools to enhance analytics workflows will be a key advantage.

Responsibilities

• Lead and contribute to custom projects focused on claims-based reporting, Patient Journeys, Market Assessment and predictive modeling using SQL/Python.
• Perform advanced data wrangling, transformation, and analysis on complex healthcare datasets, primarily in the claims domain.
• Create data-driven deliverables and visualizations to support customer engagements and business decision-making.
• Partner with Product and Customer Success teams to deliver insightful, tailored analyses to clients.
• Collaborate with global and cross-functional teams to design and implement optimized data solutions.
• Develop scalable tools such as solution workbenches and automated reporting systems.
• Scope, prioritize, and independently handle client requests with minimal supervision.
• Leverage SQL, Python, and Generative AI tools to drive efficiency, innovation, and automation in analytics workflows.
• Contribute to internal initiatives, knowledge sharing, and continuous improvement of team processes.
• Mentor and guide junior analysts, promoting best practices in coding, modeling, and data handling.

Qualifications

Bachelors or Masters degree in computer science, Statistics, Data Science, or a related
quantitative field.
• 3–5 years of hands-on experience in data science or analytics roles, with a strong focus on SQL
and Python.
• Proven expertise in healthcare data, particularly claims analytics; familiarity with pharma datasets
is mandatory.
• Strong programming skills in Python, including data manipulation, wrangling, and analysis using
libraries such as pandas, NumPy, and scikit-learn.
• Advanced proficiency in SQL for working with large, complex relational datasets.
• Comfortable working with large-scale data and able to assess existing processes to identify
opportunities for improvement.
• Sound knowledge of statistics, data modeling, and predictive analytics.
• Proficient in Microsoft Excel and experience creating clear, impactful presentations of analytical
findings.
• Strong interpersonal, communication, and presentation skills, with the ability to explain technical
concepts to non-technical stakeholders.
• Self-starter with the ability to work independently and collaboratively in a fast-paced, dynamic
environment.

ISMS Responsibilities

• Comply with information security policies and processes
• Report security weaknesses, events or potential events, or other security risks, to the organization
• Execute all tasks related to information security management system as appropriate

Why we love Analytical Wizards, and why you will too!

• Industry leading products
• Work hard, and have fun doing it
• Incredibly fast growth means limitless opportunity
• Flexible and dynamic culture
• Work alongside some of the most talented and dedicated teammates
• A collaborative and friendly culture with very high employee engagement

Job Description

We are looking for a Senior Data Scientist with a strong foundation in SQL/Python programming, data handling, and data wrangling to work on high-impact projects in the healthcare domain. This is a hands-on role involving advanced analytics, developing metrics and reports from large, complex datasets, and building scalable data solutions like solution workbenches.

The ideal candidate will demonstrate a strong aptitude for understanding business context, generating insights from data, and a proactive attitude toward learning and applying relevant data tools and techniques. A solid grasp of claims analytics, combined with the ability to work in the healthcare space and apply a wide range of quantitative and analytical methods to drive better business decisions, is essential. Experience or interest in Generative AI tools to enhance analytics workflows will be a key advantage.

Responsibilities

• Lead and contribute to custom projects focused on claims-based reporting, Patient Journeys, Market Assessment and predictive modeling using SQL/Python.
• Perform advanced data wrangling, transformation, and analysis on complex healthcare datasets, primarily in the claims domain.
• Create data-driven deliverables and visualizations to support customer engagements and business decision-making.
• Partner with Product and Customer Success teams to deliver insightful, tailored analyses to clients.
• Collaborate with global and cross-functional teams to design and implement optimized data solutions.
• Develop scalable tools such as solution workbenches and automated reporting systems.
• Scope, prioritize, and independently handle client requests with minimal supervision.
• Leverage SQL, Python, and Generative AI tools to drive efficiency, innovation, and automation in analytics workflows.
• Contribute to internal initiatives, knowledge sharing, and continuous improvement of team processes.
• Mentor and guide junior analysts, promoting best practices in coding, modeling, and data handling.

Qualifications

Bachelors or Masters degree in computer science, Statistics, Data Science, or a related
quantitative field.
• 3–5 years of hands-on experience in data science or analytics roles, with a strong focus on SQL
and Python.
• Proven expertise in healthcare data, particularly claims analytics; familiarity with pharma datasets
is mandatory.
• Strong programming skills in Python, including data manipulation, wrangling, and analysis using
libraries such as pandas, NumPy, and scikit-learn.
• Advanced proficiency in SQL for working with large, complex relational datasets.
• Comfortable working with large-scale data and able to assess existing processes to identify
opportunities for improvement.
• Sound knowledge of statistics, data modeling, and predictive analytics.
• Proficient in Microsoft Excel and experience creating clear, impactful presentations of analytical
findings.
• Strong interpersonal, communication, and presentation skills, with the ability to explain technical
concepts to non-technical stakeholders.
• Self-starter with the ability to work independently and collaboratively in a fast-paced, dynamic
environment.

ISMS Responsibilities

• Comply with information security policies and processes
• Report security weaknesses, events or potential events, or other security risks, to the organization
• Execute all tasks related to information security management system as appropriate

Why we love Analytical Wizards, and why you will too!

• Industry leading products
• Work hard, and have fun doing it
• Incredibly fast growth means limitless opportunity
• Flexible and dynamic culture
• Work alongside some of the most talented and dedicated teammates
• A collaborative and friendly culture with very high employee engagement

Want to build the next generation of AI-powered analytics and intelligent agents for observability and security use cases? Passionate about leveraging cutting-edge machine learning, large language models, and GPU-accelerated inference to transform how organizations understand and act on their logs data? Come talk with us!

As a Senior Machine Learning Engineer, you’ll build the intelligence behind the next generation of agentic AI systems that reason over massive, heterogeneous log data. You’ll combine machine learning, prompt engineering, context engineering and rigorous evaluation to create autonomous AI agents that help organizations understand and act on their data in real time.

You’ll be part of a small, high-impact team shaping how AI agents understand complex machine data. This is an opportunity to work on cutting-edge LLM infrastructure and contribute to defining best practices in context engineering and AI observability.

Location: Noida/ Bengaluru (Hybrid)

Responsibilities

• Design, implement, and optimize agentic AI components, including tools, memory management, and prompts.
• Develop and maintain golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale.
• Prototype and evaluate novel prompting strategies and reasoning chains for model reliability and interpretability.
• Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.
• Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes.
• Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement.
• Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience.

Required Qualifications

• B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field.
• 6+ years of hands-on industry experience with demonstrable ownership and delivery.
• Strong understanding of machine learning fundamentals, data pipelines, and model evaluation.
• Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn); familiarity with JVM languages is a plus.
• Working knowledge of LLM core concepts, prompt design, and agentic design patterns.
• Experience with distributed systems and dealing with large amounts of data.
• Strong communication skills and a passion for shaping emerging AI paradigms.

Desired Qualifications

• Experience leading a team of engineers.
• Prior experience building and deploying AI agents or LLM applications in production.
• Familiarity with modern agentic AI frameworks (e.g., LangGraph, LangChain, CrewAI).
• Experience with ML infrastructure and tooling (PyTorch, MLflow, Airflow, Docker, AWS).
• Exposure to LLM Ops - infrastructure optimization, observability, latency, and cost monitoring.

About Us

Sumo Logic, Inc. empowers the people who power modern, digital business. Sumo Logic enables customers to deliver reliable and secure cloud-native applications through its Sumo Logic SaaS Analytics Log Platform, which helps practitioners and developers ensure application reliability, secure and protect against modern security threats, and gain insights into their cloud infrastructures. Customers worldwide rely on Sumo Logic to get powerful real-time analytics and insights across observability and security solutions for their cloud-native applications. For more information, visit www.sumologic.com.

Sumo Logic Privacy Policy. Employees will be responsible for complying with applicable federal privacy laws and regulations, as well as organizational policies related to data protection.

Job Title: Python  Automation Expert

 About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the  British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO? 

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

Job Description:

• • Role Description:

    Hands-on engineer delivering Finance EUC automations on IT-governed platforms. Understands demand for automation, detailed requirements, and undertakes build & test, production deployment activities and RTB change implementation, following defined standards and platform guardrails. Contributes to opportunity scoping by providing technical input on feasibility and effort. Produces code, documentation and test evidence aligned to agreed closure criteria, and supports controlled deployment and post-release fixes. Works closely with the POD Lead, Finance Domain BA and platform support to ensure solutions are reliable and supportable.

     

    Skills / Knowledge / Experience:

    • Strong understanding of Python programming with Excel dependent and Pandas library, and capable of debugging Python code
    • Strong data preparation, visualization, and analytics capability
    • Design and deliver AI-assisted remediation capabilities
    • Strong understanding of EUCs (End User Computing) and their remediation through AI
    • Experience with Gen-AI tools and prompt engineering
    • Skilled in IT-managed automation platforms e.g., Alteryx
    • Knowledge of Finance data systems

Role Overview 

We’re looking for Backend Engineers to lead the design and delivery of SaaS products that are powered by data, machine learning, and AI. 

You’ll be the senior technical owner for one or more product areas, working across , backend, systems, and cloud infrastructure to: 

• Ship high-quality data/ML/AI powered features end-to-end 

• Integrate data/ML/AI capabilities into real customer workflows 

• Raise the bar on design, reliability, performance, and engineering practices across the org 

This is a hands-on senior role: you’ll write code, review designs, mentor senior engineers, and collaborate closely with product, design, data, and ML teams. 

What You’ll Do 

• Own the architecture and technical direction for key product areas in a multi-tenant SaaS platform. 

• Work with product, design, and data/ML teams to translate business problems into simple, robust technical solutions. 

• Drive the evolution of our system architecture (APIs, services, data flows, auth, tenancy, integrations) as the product and customer base scale. 

End-to-End Full-Stack Product Delivery 

• Build and maintain backend services and APIs (REST/GraphQL/gRPC) that power those experiences. 

• Deliver backend features end-to-end including data schemas and business logic. 

• Collaborate with UX and product to ensure responsive and delightful product experiences. 

Data / ML / AI Integration 

• Partner with data scientists and MLOps / platform teams to embed data, ML and AI capabilities into the product (recommendations, categorization, automation, routing, insights, LLM-powered workflows, etc.). 

• Design APIs, data contracts, and UX flows that make ML/AI features reliable, understandable, and safe for customers. 

• Ensure telemetry and feedback loops are in place so data/ML teams can measure performance, iterate models, and improve outcomes. 

• Help define and implement guardrails for AI features (fallbacks, explanations, error handling, permissions). 

Operational Excellence 

• Champion operability: monitoring, alerting, logging, and runbooks for services you own. 

• Lead efforts to improve performance, scalability, and resilience of critical paths (e.g., onboarding, reporting, AI-assisted workflows). 

• Work with security and compliance to ensure features meet requirements around authentication, authorization, data privacy, and multi-tenancy. 

• Participate in and help evolve on-call / incident response processes as a technical leader. 

Engineering Excellence & Leadership 

• Act as a technical mentor for multiple teams, raising the bar on code quality, reviews, testing, and design. 

• Lead technical design reviews and cross-team architecture discussions, especially where product, data, and ML intersect. 

• Help define engineering standards and best practices (API design, frontend patterns, error handling, observability, testing). 

• Partner with engineering management to shape roadmaps, staffing, and sequencing for major initiatives. 

What You’ll Bring 

Experience 

• 10+ years of software engineering experience 

• Demonstrated experience shipping data/ML/AI powered SaaS products, 

• Strong track record of owning and shipping complex, user-facing features end-to-end in collaboration with product management and UX. 

• Experience as a senior member of the technical staff in guiding teams and owning critical production systems. 

Technical Skills 

• Strong proficiency with at least one backend stack, for example: 

• Node.js/TypeScript, Java,  Go, Rust, or similar 

• Designing and building APIs, services, and integrations 

• Proficiency with Python and data analysis/modeling tools (e.g. pandas/pytorch) 

• Solid understanding of data modeling and storage: relational databases, caching, and basic data warehousing concepts. 

• Familiarity with data/ML/AI concepts: 

• How ML models or LLMs are exposed as services 

• Typical failure modes, latency/throughput considerations, and guardrails 

• Experience with cloud platforms (AWS / GCP / Azure), containers, and infrastructure (networking, scaling, security). 

• Strong habits around testing, CI/CD, code reviews, and incremental delivery. 

Mindset & Soft Skills 

• Product-minded engineer who cares about customer problems, usability, and outcomes, not just code. 

• Systems thinker who can balance short-term delivery with long-term architectural health. 

• Excellent communicator, comfortable driving alignment across engineering, product, data, and go-to-market teams. 

• Enjoys mentoring and multiplying the impact of other engineers. 

Role Overview 

We’re looking for Backend Engineers to lead the design and delivery of SaaS products that are powered by data, machine learning, and AI. 

You’ll be the senior technical owner for one or more product areas, working across , backend, systems, and cloud infrastructure to: 

• Ship high-quality data/ML/AI powered features end-to-end 

• Integrate data/ML/AI capabilities into real customer workflows 

• Raise the bar on design, reliability, performance, and engineering practices across the org 

This is a hands-on senior role: you’ll write code, review designs, mentor senior engineers, and collaborate closely with product, design, data, and ML teams. 

What You’ll Do 

• Own the architecture and technical direction for key product areas in a multi-tenant SaaS platform. 

• Work with product, design, and data/ML teams to translate business problems into simple, robust technical solutions. 

• Drive the evolution of our system architecture (APIs, services, data flows, auth, tenancy, integrations) as the product and customer base scale. 

End-to-End Full-Stack Product Delivery 

• Build and maintain backend services and APIs (REST/GraphQL/gRPC) that power those experiences. 

• Deliver backend features end-to-end including data schemas and business logic. 

• Collaborate with UX and product to ensure responsive and delightful product experiences. 

Data / ML / AI Integration 

• Partner with data scientists and MLOps / platform teams to embed data, ML and AI capabilities into the product (recommendations, categorization, automation, routing, insights, LLM-powered workflows, etc.). 

• Design APIs, data contracts, and UX flows that make ML/AI features reliable, understandable, and safe for customers. 

• Ensure telemetry and feedback loops are in place so data/ML teams can measure performance, iterate models, and improve outcomes. 

• Help define and implement guardrails for AI features (fallbacks, explanations, error handling, permissions). 

Operational Excellence 

• Champion operability: monitoring, alerting, logging, and runbooks for services you own. 

• Lead efforts to improve performance, scalability, and resilience of critical paths (e.g., onboarding, reporting, AI-assisted workflows). 

• Work with security and compliance to ensure features meet requirements around authentication, authorization, data privacy, and multi-tenancy. 

• Participate in and help evolve on-call / incident response processes as a technical leader. 

Engineering Excellence & Leadership 

• Act as a technical mentor for multiple teams, raising the bar on code quality, reviews, testing, and design. 

• Lead technical design reviews and cross-team architecture discussions, especially where product, data, and ML intersect. 

• Help define engineering standards and best practices (API design, frontend patterns, error handling, observability, testing). 

• Partner with engineering management to shape roadmaps, staffing, and sequencing for major initiatives. 

What You’ll Bring 

Experience 

• 10+ years of software engineering experience 

• Demonstrated experience shipping data/ML/AI powered SaaS products, 

• Strong track record of owning and shipping complex, user-facing features end-to-end in collaboration with product management and UX. 

• Experience as a senior member of the technical staff in guiding teams and owning critical production systems. 

Technical Skills 

• Strong proficiency with at least one backend stack, for example: 

• Node.js/TypeScript, Java,  Go, Rust, or similar 

• Designing and building APIs, services, and integrations 

• Proficiency with Python and data analysis/modeling tools (e.g. pandas/pytorch) 

• Solid understanding of data modeling and storage: relational databases, caching, and basic data warehousing concepts. 

• Familiarity with data/ML/AI concepts: 

• How ML models or LLMs are exposed as services 

• Typical failure modes, latency/throughput considerations, and guardrails 

• Experience with cloud platforms (AWS / GCP / Azure), containers, and infrastructure (networking, scaling, security). 

• Strong habits around testing, CI/CD, code reviews, and incremental delivery. 

Mindset & Soft Skills 

• Product-minded engineer who cares about customer problems, usability, and outcomes, not just code. 

• Systems thinker who can balance short-term delivery with long-term architectural health. 

• Excellent communicator, comfortable driving alignment across engineering, product, data, and go-to-market teams. 

• Enjoys mentoring and multiplying the impact of other engineers. 

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…..

We’re hiring Applied ML Engineers to partner with multiple product teams to extract insights from data and build AI-powered features and automated workflows across the product suite. 

In this role, you will both: 

• Enable product teams: teach, coach, and guide them on data and ML best practices 

• Lead by example: do complex data analysis and ML modeling, architecture, and implementation work as needed to accelerate teams while mentoring more junior data/ML folks. 

You’ll own the data analysis, ML modeling, and workflow logic that let AI understand user requests, enrich and route them, suggest actions, and in some cases fully automate resolution.  

What You’ll Do 

Data & ML Modeling 

• Explore and analyze data using Python, pandas, and PySpark (or similar tools). 

• Use matrix factorization, clustering, dimensionality reduction, and related techniques to understand and prepare data for modeling, and to identify and label latent factors (e.g., user behavior patterns, content/topic clusters, expertise dimensions). 

• Create, tune, and productionize ML models for: 

• Categorization / classification 

• Recommendations and similarity 

• Other prediction or ranking tasks that power product features 

AI-Powered Workflows & Features 

• Design and implement AI-driven ingest flows that turn unstructured inputs (tickets, emails, forms, messages, logs, etc.) into well-structured data that models and downstream systems can use. 

• Build workflows where AI can: 

• Auto-fill or suggest key fields and metadata. 

• Proactively ask users/customers for missing or ambiguous information (e.g., via email or messaging). 

• Surface similar past items or solutions to assist humans in decision-making. 

• Fully handle simple, repetitive “Level 1” style requests end-to-end when safe to do so. 

• Work closely with engineers to integrate models and workflows into production systems with proper monitoring, fallbacks, and guardrails. 

Cross-Team Leadership & Enablement 

• Work with multiple product teams to help them identify and scope AI opportunities in their areas. 

• Define patterns, templates, and best practices for data ingestion, feature creation, model usage, and evaluation that teams can reuse. 

• Serve as a trusted advisor and technical lead: 

• Provide design and architecture guidance on data and ML-heavy features. 

• Join projects to handle the most complex modeling or workflow automation pieces when teams get stuck. 

• Mentor and guide junior data/ML engineers and analysts: 

• Conduct code and model reviews. 

• Pair with them on tricky problems. 

• Help them develop good intuitions about metrics, evaluation, and operational reliability. 

• Help establish and socialize standards for experimentation, documentation, and responsible AI usage across teams. 

What You’ll Bring 

Core Skills 

• 5+ years in data science, ML engineering, or a similar applied role, with a strong record of shipping production data/ML features. 

• Strong Python skills and experience with pandas for data analysis. 

• Experience with PySpark or other distributed data processing frameworks. 

• Solid understanding of ML fundamentals, including: 

• Supervised learning and classification models 

• Matrix factorization / embeddings / latent factor models 

• Feature engineering and model evaluation (offline metrics and online experiments) 

• Proficiency with PyTorch (or a similar deep learning framework) and related ML tooling. 

• Strong SQL and experience with modern data warehouses / data lakes. 

• Comfort working with APIs, microservices, and production integration of ML models, including performance and reliability considerations. 

Leadership & Collaboration 

• Experience serving as a technical lead or senior individual contributor across multiple teams or projects. 

• Proven ability to translate business problems into data/ML projects, and to clearly explain tradeoffs to non-ML stakeholders. 

• Track record of mentoring junior engineers/analysts and improving team practices (e.g., review culture, testing, monitoring). 

• Strong communication skills and the ability to drive alignment across product, engineering, and operations. 

Nice to Have 

• Experience with LLMs and language-centric workflows (RAG, prompt engineering, fine-tuning, tool/agent orchestration). 

• Experience building agent-assist features or automated workflows in operational or customer-facing products. 

• Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Vertex, etc.) and production model monitoring. 

• Prior experience in a platform/enablement role, supporting many product teams with shared data and ML capabilities. 

Business Overview 

IPG Mediabrands is the media and marketing solutions division of Interpublic Group (NYSE: IPG). IPG Mediabrands manages over $47 billion in marketing investment globally on behalf of its clients across its full-service agency networks UM, Initiative and Mediahub and through its award-winning specialty business units Healix, Kinesso, MAGNA, Mediabrands Content Studio, Orion Holdings, Rapport, and the IPG Media Lab. IPG Mediabrands clients include many of the world’s most recognizable and iconic brands from a broad portfolio of industry sectors including automotive, personal finance, consumer product goods (CPG), pharma, health and wellness, entertainment, financial services, energy, toys and gaming, direct to consumer and e-commerce, retail, hospitality, food and beverage, fashion and beauty. The company employs more than 18,000 diverse marketing communication professionals in more than 130 countries. Learn more at www.ipgmediabrands.com. 

Position Overview 

We are looking for a savvy Reporting and Analytics Manager to manage in-progress and upcoming data infrastructure projects. The candidate will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder using Python and data wrangler who enjoys optimizing data systems and building them from the ground up. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products.

Responsibilities

Create and maintain optimal data pipeline architecture, assemble large, complex data setsthat meet functional / non-functional business requirements using Python and SQL / AWS / Snowflakes.

 • Identify, design, and implement internal process improvements through: automating manual processes using Python, optimizing data delivery, re-designing infrastructurefor greater scalability, etc.

• Build the infrastructure required for optimal extraction, transformation, and loading ofdata from a wide variety of data sources using SQL / AWS / Snowflakes technologies.

• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.