Role

We are looking for an experienced Staff Machine Learning Engineer to join our Engineering team. This role is based in Hyderabad, reporting to the Senior Director, Engineering. You will be responsible for building and maintaining large-scale distributed systems that power our entire ML pipeline, from data collection to real-time serving. You’ll solve complex real-world business problems by partnering closely with data scientists and product teams to deliver impactful automation and intelligence. You will also help design and build Agentic AI systems—developing and orchestrating specialized agents to automate and scale ZPA segmentation workflows, from signal ingestion and reasoning to policy recommendations and enforcement validation.

What you’ll do (Role Expectations)

• Build and maintain large-scale distributed systems to support the whole pipeline including data collection, feature engineering, model training, model evaluation, model deployment, and real-time serving—including Agentic AI components (agent workflows, orchestration, tool integrations, and real-time agent serving).
• Develop functional specifications, assess task requirements and scheduling, and participate in the development, debug, and support—including designing agent behaviors, evaluation strategies (quality/safety/latency), and rollout/monitoring plans for agent-based systems.
• Solve complex real-world business problems like threat detection and business intelligence by working closely with stakeholders including data scientists, product management, and product engineering teams—including building multi-agent solutions that automate analysis and decisioning (e.g., recommendation, triage, and segmentation/policy workflows).

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.
• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.
• You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.
• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.
• You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking for (Minimum Qualifications)

• 4+ years of experience as a AI-ML Engineer
• Experience with applying machine learning for improving key business metrics, optimized models for accuracy, latency
• Experience with researching newer techniques, and innovating for building ML based solutions
• Experience with algorithms in building out data collection/processing infrastructure, Machine Learning model training, and serving platforms
• Expertise in leveraging and augmenting LLM models for software development

What Will Make You Stand Out (Preferred Qualifications)

• Proven track record of designing, building and shipping end-end applications at scale
• Experience identifying and solving problems in data using machine learning systems
• Familiarity with multi-agent systems, agent architectures, prompt engineering and SOTA AI frameworks

#LI-Hybrid #LI-AN4

App Framework Team • 80% Backend / 20% Frontend • 8+ Years

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that unifies identity, intelligence, and omnichannel activation into a single platform – powered by trillions of consumer signals and one of the industry’s largest proprietary databases. Our enterprise clients use the Zeta Marketing Platform (ZMP) to personalize experiences at the individual level across every channel.

The App Framework team is building something foundational: an Agentic App Builder platform on top of ZMP that enables teams across Zeta to develop, deploy, and operationalize applications that integrate with ZMP’s core capabilities – identity, intelligence, activation, and measurement. Think of it as the platform that powers the next generation of applications at Zeta, with AI and agentic workflows built into the development experience itself.

As a Lead Full Stack Engineer, you’ll shape the architecture of this platform from the ground up. You’ll partner with product owners and engineering teams across the organization to understand what application builders need, design the backend services and APIs that make it possible, and build the frontend experiences that make it intuitive. You’ll own what you build end-to-end – from requirements through production operations – with a focus on architectural simplicity, developer experience, and operational excellence.

We develop using AI-assisted workflows (Cursor, Claude Code) and ship through continuous delivery. This is a rare opportunity to build a platform that fundamentally changes how applications are created at an enterprise scale.

What you’ll Do:

• Design and build the Agentic App Builder platform – the services, APIs, and developer tools that enable teams to create, deploy, and manage applications on top of ZMP fast and at scale.
• Build intuitive frontend experiences in React/TypeScript that make the platform accessible and productive for application builders.
• Ship continuously and confidently through CI/CD, with observability, resilience and reliability built in from the start.
• Embed AI/LLM capabilities into the platform to enable agentic application development and intelligent automation.
• Use AI-assisted development tools as a core part of your workflow to accelerate delivery while maintaining high quality.
• Collaborate with teams across Zeta to gather requirements, align on integration patterns, and ensure the platform meets real-world application needs.
• Mentor engineers, lead technical initiatives, and help establish the engineering practices and standards for the platform.

What We’re Looking For:

8+ years of software engineering with a track record of building and operating platform-level systems. You’re deeply proficient in at least two of Python, Java, Ruby, or Node.js, with solid React/TypeScript skills on the frontend. You understand what it takes to build developer-facing platforms in the age of AI.

You bring hands-on experience with AWS services and you’re comfortable operating in multi-tenant, compliant environments. Continuous delivery, test-driven development, and agile are disciplines you practice with conviction. You’re already using AI-assisted coding tools and you’re excited about building platforms that leverage agentic workflows.

You’re a strong communicator who thrives on cross-team collaboration. You enjoy working with product owners to define problems, proposing architectures, building alignment, and then delivering. You bring energy and curiosity to your work, and you elevate the people around you.

Nice to Have:

• Experience building agentic developer platforms, internal tooling, or app builder/low-code systems.
• MarTech or AdTech domain knowledge (DSPs, bid stream processing, data-intensive platforms).
• Familiarity with our data stores: MySQL, Snowflake, Aerospike, DynamoDB, S3.
• Experience designing plugin architectures, SDK/API frameworks, or extensible platform systems.

Tech Stack:

Why You’ll Love It Here:

• Build a foundational platform that shapes how every application at Zeta gets created – high-impact, high-visibility work from day one.
• AI-native engineering culture – agentic development is how we build, and you’ll be building the platform that brings it to others.
• Real ownership and autonomy. We trust our engineers to make great decisions and give them the space to do it.
• Collaborative, low-ego team that genuinely enjoys working together and learning from each other.
• Public company (NYSE: ZETA) with strong growth, competitive compensation, equity, and comprehensive benefits.

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

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.

Truveta provides unprecedented real-world data and real-time intelligence, powered by a dataset built with and owned by US health systems united in a mission of Saving Lives with Data. Together, we power breakthrough medical discoveries, accelerate regulatory-grade evidence, and improve patient care. Today, Truveta enables research on more than 130 million de-identified patients across the US.  

Achieving Truveta’s ambitious mission requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values. 

Role Overview

We are hiring a Prompt Engineer with a strong clinical informatics background to build and optimize AI prompts for healthcare and clinical data applications. This role requires hands-on clinical understanding, experience working with real clinical data, experience writing prompts for AI models, and the ability to align LLM prompts with underlying clinical data models.

You will work closely with clinicians, data engineers, and AI teams to translate clinical questions and workflows into accurate, safe, and scalable AI interactions.

Key Responsibilities

• Design, test, and optimize prompts for LLM-based clinical use cases such as:
• Cohort identification
• Clinical question answering
• Concept extraction
• Clinical code mapping
• Translate clinical requirements into structured prompts aligned with clinical data schemas
• Collaborate with data engineers to understand how diagnoses, labs, medications, encounters, and outcomes are modeled
• Evaluate AI outputs for clinical accuracy, relevance, bias, and safety
• Apply healthcare data standards (FHIR, SNOMED CT, LOINC, RxNorm, ICD-10-CM) within prompt logic and validation
• Create prompt evaluation criteria and quality benchmarks
• Document reusable prompt patterns and best practices
• Continuously improve prompts based on model behavior and user feedback.

Required Qualifications

• 2–5 years of experience in clinical informatics, healthcare analytics, or health IT
• Clinical background required, such as:
• Nursing, pharmacy, medicine, public health, or clinical informatics
• OR hands-on experience working with clinical workflows or EHR data
• Strong understanding of clinical data modeling, including representation of:
• Diagnoses, procedures, medications
• Laboratory results and vitals
• Encounters and outcomes
• Practical experience with healthcare data standards:
• FHIR
• SNOMED CT
• LOINC
• RxNorm
• ICD-10-CM
• Hands-on experience with LLMs and prompt engineering for applied or production use cases
• Ability to critically evaluate AI outputs for correctness and clinical safety
• Strong analytical, documentation, and communication skills

Preferred

• Experience with clinical NLP or unstructured clinical text
• Familiarity with EHR systems or clinical data repositories
• Working knowledge of Python for prompt testing or evaluation
• Working knowledge of SQL for exploring clinical datasets
• Experience combining structured and unstructured healthcare data
• Prior work on healthcare AI, decision support, or analytics platforms

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. 

Working alongside our affiliated law firms with Envoy, we are giving companies the tools they need to hire the best talent from around the world, send talent where it’s needed, and help support foreign workers and immigrants throughout the process. We’re a fast-growing, award-winning technology company, a leader in our space and are backed by some of the country’s leading venture capital and growth equity firms.

As a result of continued growth, we are currently hiring Senior Immigration Specialist to work within our office in Hyderabad, India. These role require a seasoned professional with strong immigration background, specifically in the field of US business/corporate immigration - this means, your experience will be skewed towards the processing of US employment-based visa applications. 

As our Senior Immigration Specialist, you will be required to:

• Communicate and understand the US immigration requirements of clients both individuals and corporates
• Work across the following types of visas: EB-1/2/3, O-1, NIW, dependent and derivative cases, advance parole and work authorizations, AOS, and all phases of the employment-based Green Card processes
• Manage visa applications from initiation through completion, overseeing the full application lifecycle, consistently focus on improving accuracy while processing visa applications
• Maintain knowledge of industry changes and any amendments to US immigration laws
• Maintain an accurate record of cases and provide periodic updates as required
• Remain aware of regular USCIS updates
• Proactively identify the opportunities for process/ system improvement and work closely with lead, Technology QA and Development teams to implement
• Work closely with the inhouse technology teams to develop and improve our technology products, as and when required

To apply for this role, you should possess the following skills, experience and qualifications:

• Possess hands on experience in processing the complete end to end EB-1A/B/C, O-1, Green Card petition drafting and LCA preparation in DOL and maintaining data with the high quality
• Willing to work in shifts
• Excellent verbal and written communication skills; English grammar must be excellent
• Highly organized and detail oriented with ability to effectively multi-task
• Strong client / customer focus and a team approach
• 4 to 8 years of experience within employment-based immigration, preferably in a large high volume law firm environment
• LLB/LLM from accredited college or university.

If this role excites you, please take a moment to complete the questionnaire below and attach your current resume. We look forward to your prompt response.

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.

Position Summary

Arcesium seeks an experienced Data Scientist professional to join our Business Operations team within the Client and Partner Development (CPD) organization. The ideal candidate will be comfortable working across large volumes of varied datasets spanning pricing, headcount, market research, commercial performance, and translating that data into the models, frameworks, and insights that drive decision-making. Beyond building models and reporting on data, this person will be expected to draw principled conclusions from their analysis and present clear, strategic recommendations to senior leadership. You will also play an active role in identifying AI-driven solutions that improve how the team works and be a part of AI strategy for CPD. You will collaborate closely with global CPD teams across Sales & Partnership, Revenue Operations, Marketing, Forward Deployed, Account Management and Client Success, Service and Solutions teams to execute complex projects and help the organization scale through data-backed governance.

What you'll do:

• Identify relevant data sources and work with CPD stakeholders across functions to collect, analyze, and interpret large structured and unstructured datasets spanning domains such as pricing, headcount, market research, and operational metrics.
• Devise and apply algorithms and models to extract insight from large data stores. Conduct data and error analysis to improve model performance, and clean and validate data for uniformity and accuracy.
• Analyze data for trends and patterns with clear objectives in mind. Interpret outputs and draw principled conclusions rather than stopping at the analysis itself, ensuring findings inform real decisions.
• Implement analytical models and reporting frameworks end to end, from data ingestion through to leadership-ready outputs.
• Conduct what-if and scenario analyses and translate outputs into clear narratives that are actionable at the senior leadership level.
• Design and develop automation scripts and data pipelines to synthesize and structure data from diverse sources, applying critical thinking to move toward zero-touch processes and maximize end-to-end efficiency.
• Produce KPI dashboards and performance reports using historical data to surface trends and productivity insights for executive audiences, with a focus on telling the story behind the data.
• Act as the primary internal champion for responsible, practical AI use within CPD, educating stakeholders, setting best practices, and ensuring solutions are sustainable and governed.
• Develop reusable AI frameworks, prompt libraries, and automation components that scale adoption across the CPD organization and serve as a foundation for future capabilities.

What you'll need:

• Strong verbal and written communication skills, with the ability to present analytical findings clearly to senior leadership and stakeholders across functions.
• 4 to 7 years of experience in a data analytics or business operations role. Prior experience at a financial technology firm is a plus.
• Advanced proficiency in Excel including complex formulas and VBA Macro programming. Strong Excel fundamentals are a core expectation of this role.
• Proficiency in Python or similar scripting languages for data transformation, automation, and analysis.
• Working knowledge of SQL for querying and managing structured datasets.
• Experience with data visualization tools, particularly Power BI, to build dashboards and reports for executive and operational audiences.
• Experience with data mining and statistical analysis, including segmentation techniques and statistical packages for working with large datasets.
• Proven ability to conduct what-if and scenario analysis and communicate implications clearly to non-technical senior stakeholders.
• Experience tracking KPIs and relevant metrics for revenue organizations, aligned with broader organizational performance indicators.
• Demonstrated hands-on experience building AI-powered workflows, automation pipelines, or LLM-assisted tools in a business context.
• Genuine intellectual curiosity about AI and a track record of applying it to real operational problems.
• Ability to balance medium to long-term analytical projects alongside day-to-day operational responsibilities.

Arcesium's Personal Data Privacy Notice for Candidates is linked here. 

About the Company 

At Redpin, we simplify life’s most important payments. Buying a property overseas can be stressful—especially when it comes to moving money. Through our Currencies Direct and TorFX brands, we’ve been helping customers do exactly that for over 25 years.

With recent investment, we are building a new generation of digital products and services that make international real estate payments simpler, faster, and more transparent.

As part of Redpin 2.0, we are transforming from a horizontal FX platform into a verticalized, embedded software company, positioning ourselves as the global solution for real estate payments.

About the Role

At Redpin, this role is not just about managing infrastructure — it’s about building intelligent, scalable, and developer-first platforms that power our next-generation digital products.

As a Senior Software Engineer – DevOps, you will play a hands-on role in designing, building, and operating cloud-native infrastructure and DevOps platforms, with a strong emphasis on automation, reliability, security, and cost efficiency.

We are looking for a DevOps Engineer with exposure to AI/ML or Generative AI use cases, who can help us embed intelligence into our engineering ecosystem — from pipelines to observability and platform operations.

What You'll Do

AI / ML / GenAI

• Hands-on experience with platforms such as OpenAI, Bedrock, or Vertex AI
• Strong understanding of prompt engineering and AI API integrations
• Solid foundation in machine learning concepts and LLM architectures

Cloud Infrastructure (AWS)

• Design and implement AI-powered automation solutions for DevOps and platform engineering use cases
• Build and integrate AI agents to enhance developer productivity
• Develop and maintain CI/CD pipelines with AI-assisted workflows
• Design, provision, and operate secure, scalable AWS infrastructure
• Work across compute, networking, storage, and IAM
• Support multi-account AWS environments and apply governance guardrails
• Implement Infrastructure as Code (IaC) using Terraform and/or CloudFormation
• Troubleshoot and resolve cloud infrastructure issues

CI/CD & DevOps Automation

• Build, maintain, and optimize CI/CD pipelines for application and microservices teams (preferably using GitLab or GitHub)
• Automate build, test, security scanning, and deployments
• Implement deployment strategies such as blue-green, canary, and rolling deployments
• Improve pipeline performance, stability, and developer experience

Cloud Security & Governance (Execution Focus)

• Implement AWS security best practices including IAM, VPC security, encryption, and secrets management
• Enforce tagging standards, access controls, and policy guardrails
• Integrate security scanning (SAST, DAST, container scanning) into CI/CD pipelines
• Support audit and compliance requirements

Reliability & Observability

• Implement and manage monitoring, logging, and alerting solutions
• Build dashboards for system health, availability, and performance
• Improve system reliability through automation and proactive monitoring

Cloud Cost Optimization

• Monitor and optimize AWS costs across services.
• Implement right-sizing, autoscaling, and storage lifecycle policies.
• Support Savings Plans and Reserved Instance optimization.
• Promote cost-efficient cloud usage and architecture

DevOps Best Practices

• Apply and promote DevOps principles such as automation, CI/CD, and IaC.
• Reduce operational toil through tooling and automation.
• Support teams in adopting cloud-native and DevOps best practices

Collaboration & Mentorship

• Work closely with application, SRE, and security teams.
• Mentor junior DevOps engineers through code reviews and hands-on guidance.
• Contribute to documentation, runbooks, and operational standards

What You’ll Need

• Strong hands-on experience with AWS (EC2, EKS, ECS, VPC, IAM, RDS, S3, CloudWatch)
• Experience building AI agents or automation bots
• Familiarity with MLOps and FinOps practices
• Strong scripting skills (Python or Bash)
• Proven experience with CI/CD tools (GitLab CI, GitHub etc.)
• Strong experience with Infrastructure as Code (Terraform preferred)
• Hands-on experience with Docker and Kubernetes (EKS)
• Solid understanding of Linux, networking, and cloud security
• Experience with monitoring, logging, and alerting systems
• Strong troubleshooting and automation skills

Bonus Points

•  AWS Config, CloudTrail, GuardDuty
• Observability tools (Corologix, ELK, Datadog)
• GitOps tools (ArgoCD, Flux)
• Scripting skills in Python, Go, or Bash
• Exposure to FinOps practices
• AWS Certified Solutions Architect – Associate or Professional

We welcome people from all backgrounds who seek the opportunity to help build a future where we connect the dots for international property payments. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world of PropTech forward together.

Redpin, Currencies Direct and TorFX are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, colour, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.

ABOUT THE ROLE:

Tide is hiring a Senior Staff Software Engineer to lead the architecture of our agentic platform. You will shape the shared capabilities that allow AI systems to operate safely, reliably, and at scale across Tide. That includes context, orchestration, tool execution, trust controls, observability, and evaluation. You will participate in key build versus buy decisions, integrate external components where they accelerate us, and ensure we own the parts that matter most for Tide’s trust, data advantage, and long-term platform leverage.

As a Senior Staff Engineer you’ll: 

• Define the architecture for Tide’s agentic platform
• Drive the design of shared services such as context APIs, tool layers, policy controls, and auditability 
• Partner with product, data, security, and engineering teams to turn use cases into reusable platform capabilities
• Set standards for reliability, safety, scalability, and developer experience
• Provide technical leadership across teams and unblock critical decisions
• Implement cost-management and routing logic to optimize LLM spend across different providers
• Design and build automated evaluation pipelines to measure agent reasoning accuracy and safety trajectories 

WHAT WE ARE LOOKING FOR:

• Deep experience building platform or infrastructure systems at scale
• Strong judgement across APIs, distributed systems, data, and cloud-native architecture
• Track record of leading complex cross-team technical problems
• Experience integrating third-party platforms without losing control of core architecture
• Strong understanding of reliability, security, and observability
• Experience with AI platform components is valuable, but not essential
• Experience in highly regulated industries (Fintech, Healthtech, etc.) where safety and compliance are core to the product is highly desirable 

Our Tech Stack:

• Java, Spring Boot and JOOQ to build the RESTful APIs of our microservices (but we welcome people who are used to any strongly typed general purpose programming language!)
• Event-driven architecture with messages over SNS+SQS and Kafka to make them reliable
• Primary datastores are MySQL and PostgreSQL via RDS or Aurora (we are heavy AWS users)
• Docker, Terraform, EKS used by the Cloud team to run the platform
• DataDog and Rollbar to keep it running
• GitHub with Sonarcloud, Semgrep and solid testing to power the CI/CD pipelines - new joiners are encouraged to have something deployed to production in their first 2 weeks
• Angular 2+ with ngrx on Web, Flutter for the Mobile App
• Fivetran/Snowflake/Looker for the BI insights and Python/Faust/Flask/Tecton + some ML libs for the automated decisioning and risk management

WHAT YOU’LL GET IN RETURN: 

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

Truveta provides unprecedented real-world data and real-time intelligence, powered by a dataset built with and owned by US health systems united in a mission of Saving Lives with Data. Together, we power breakthrough medical discoveries, accelerate regulatory-grade evidence, and improve patient care. Today, Truveta enables research on more than 130 million de-identified patients across the US.  

Achieving Truveta’s ambitious mission requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values. 

Who We Need  

Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. We are seeking candidates inspired by the opportunity to securely apply data in the development of real-world health solutions. Beyond core capabilities, we seek problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference.  We do things the right way. Our commitment to security and compliance assurance cannot be stressed enough. This position is critical to ensuring we are successful. 

If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.  

This Opportunity  

The successful candidate will design and support solutions that support the company’s Digital Workplace strategy. They will work on leading edge technologies that help modernize endpoint management by leveraging the cloud to quickly deliver end-user improvements. 

Responsibilities: 

• Device Management: Define, implement and maintain endpoint hardening baselines for Windows, macOS, and Linux systems with MDM such as Microsoft Intune, and JAMF. 

• Policy & Hardening: Develop and enforce security policies, standards, and procedures for all endpoint devices. Implement system hardening configurations based on industry best practices. 

• Deploy & Manage Security Tools: Implement, configure, and maintain endpoint security solutions, including Endpoint Detection and Response (EDR), Extended Detection and Response (XDR), antivirus/anti-malware software, and host-based firewalls. 

• Incident Response: Collaborate with IT and Security team to respond to endpoint-related incidents. Triage, remediate, and contain security incidents and threats on endpoints. Perform forensic analysis when necessary. 

• Vulnerability Management: Manage the endpoint vulnerability lifecycle, from discovery and assessment to remediation, using scanning tools and patch management systems. 

• Patch Management: Design and oversee the deployment of updates, security patches for operating system and applications. 

• Automation & Scripting: Develop scripts and automation (e.g., using Python, PowerShell) to streamline security operations, automate repetitive tasks, and improve response times. 

• AI Protection: Secure endpoints used for AI development, including devices accessing model weights, training data, and production inference systems, implementing guardrails on AI tool usage (e.g., prompt injection prevention in local LLM dev tools, restricted plugins/add-ons). 

• Data Loss Prevention: Enforce data loss prevention (DLP) and encryption policies on devices used to handle sensitive AI training datasets, including PHI/PII and proprietary corporation data. 

• On-call: Ability to participate in On-call rotation. 

• On-site: This position requires daily onsite work at Truveta office in Hyderabad. 

Qualifications 

• Experience: 3-5+ years of hands-on experience in an endpoint security, cybersecurity engineering, or similar role. 

• Technical Proficiency: Deep understanding of modern operating systems (Windows, macOS) and their architecture, configuration and deployment in a large enterprise environment. 

• Cloud Experience: Strong hands-on experience on Azure Cloud PC, VM, Azure Firewall and Azure Networking. 

• MDM Expertise: Strong hands-on experience on Microsoft Intune and JAMF administration, such as device enrollment, OS upgrade/patch, configuration, profile.  

• Policy Management: Define and assign compliance/security policies to ensure corporation devices meet organizational security standards. 

• Application Management: Strong hands-on experience on applications control, deployment, patch and upgrade. 

• EPM: Proven experience with industry-leading EPM platforms such as CyberArk and BeyondTrust to control user privileged access and provide advanced threat protection and vulnerability management. 

• Networking: Solid understanding of TCP/IP IPv4/v6, experience of office network (Routing / Switching / WAN, Wi-Fi & Security) management and network security concepts. 

• Security Principles: Strong knowledge of cybersecurity frameworks (e.g., NIST, MITRE), threat intelligence, and incident response methodologies.  

• Compliance: Experiences with SOC 2 Type 2, HITRUST, and ISO compliance frameworks. Interact with the compliance team to ensure the company compliant and remediate gaps during compliance finding and controls. 

• Collaboration: Excellent verbal and written communication/presentation, ability to explain complex technical concepts to both technical and non-technical audiences. 

Why Truveta?   

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional, and everything in between. Join us as we build an amazing company together.   

We offer:   

• Interesting and meaningful work for every career stage   

• Competitive compensation   

• Comprehensive benefits with strong medical, dental, and vision insurance plans  

• 401K plan  

• Professional development for continuous learning   

• Work/life autonomy via flexible work hours and flexible paid time off  

• Generous parental leave  

• Regular team activities (virtual and in-person as soon as we are able)  

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contactors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements. 

About Truveta 

Truveta is the world’s first health provider–led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’s ambitious vision requires an incredible team of talented and inspired people with a unique combination of health, software, and big data expertise who share our company values. 

 
Who We Need 

Truveta is seeking Senior Full Stack Engineers in India to help build and evolve our internal annotation and administrative platforms. These systems are critical to enabling high-quality data modeling, clinical note annotation, LLM-based labeling, concept mapping, and operational workflows across the company. 

We are looking for engineers who enjoy solving complex UX and data problems and want to build tools used daily by internal experts. 

This Opportunity 

As a Senior Full Stack Engineer, you will work on modern internal web applications that handle large volumes of text, structured and unstructured data, and complex review workflows. You will collaborate closely with engineers, product managers, designers, and ML teams across geographies. 

What You’ll Do 

• Design, build, and maintain full-stack features for annotation and internal tooling platforms. 

• Implement advanced UI interactions such as text highlighting, tagging, categorization, and review workflows. 

• Build backend services that support annotation workflows, metadata management, and integrations. 

• Collaborate with ML engineers to translate annotation requirements into scalable software solutions. 

• Optimize performance for high-volume data and concurrent users. 
  
  
• Participate in code reviews, architecture discussions, and on-call rotations as needed. 

Key Qualifications 

• Bachelor’s degree in Computer Science or equivalent experience. 

• 8+ years of professional software development experience. 

• Strong frontend experience with React and TypeScript. 

• Experience with state management frameworks such as Redux. 

• Backend experience using NestJS (Node.js) and/or C#/.NET. 

• Familiarity with RESTful API design and modern service architectures. 

• Experience building internal tools, dashboards, or workflow-driven applications. 

• Strong collaboration and communication skills. 

 Senior Commercial Product Manager - Credit 

The Senior Commercial Product Manager for Credit owns the commercial lifecycle of Billtrust’s credit product portfolio, spanning AI-powered risk assessment, customer credit scoring, and intelligent credit decisioning solutions. This role drives products from ideation through adoption collaborating with internal stakeholders, engineering teams, and directly with customers to define requirements, prioritize the roadmap, and deliver successful go-to-market outcomes. 
 
The ideal candidate is a proactive, natural problem solver who bridges complex technical capabilities and real customer value — and who actively uses AI tools as part of how they work. We’re looking for someone who doesn’t just understand AI as a product category, but who applies it personally: to research, synthesize information, build artifacts, and think through problems faster. This person communicates with clarity and confidence across all settings, from executive 
presentations to customer webinars. 

What You'll Do 

• Own the Credit product portfolio end-to-end — serve as the subject matter expert and primary liaison across revenue, engineering, and customer-facing teams; maintain a prioritized backlog with each sprint aligned to business and customer outcomes 

• Proactively surface gaps and opportunities in the credit workflow before problems escalate, and evaluate incoming feature requests based on market demand, ROI, and customer impact— without needing to be directed 

• Lead external customer presentations, product webinars, and in-person meetings to clearly articulate capabilities, roadmap direction, and ROI; deliver equally compelling internal presentations to senior leadership on product performance, strategic tradeoffs, and investment priorities 

• Own the Credit product scorecard and annual planning baseline — track KPIs including decisioning accuracy, automation rates, and customer health; define tradeoffs and present clear investment options to leadership 

• Build strong client relationships to co-develop capabilities and validate product decisions; partner with Sales and Customer Success on value narratives and enablement content that drive adoption of Credit AI features 

• Collaborate with engineering leads to define requirements, design functionality, and drive 
  delivery from analysis through implementation across a high volume of concurrent initiatives 

• Help shape where and how AI capabilities get embedded into the Credit product — identifying high-value opportunities for intelligent automation, rise decisioning enhancements, and AI-assisted workflows within the product experience 

• Use AI tools as a core part of how you work — synthesizing market signals, accelerating competitive research, drafting PRDs and briefs, and prototyping concepts faster than traditional methods 

• Mentor other product managers and actively share effective AI practices that raise team output quality and speed 

Experience & Technical Background:  

• 10+ years of product management experience; bachelor’s degree in Computer Science, MIS, Business, or equivalent 

• Domain experience in financial technology, credit decisioning, accounts receivable, or payments — with strong attention to detail 

• Exceptional communication skills — written and verbal — with a proven ability to present confidently to C-suite stakeholders, customers, and prospects; demonstrated experience with external presentations, webinars, and user forums 

• Proactive self-starter: you identify issues before they surface, take ownership without being directed, and drive ambiguous situations toward clarity 

• Demonstrated, hands-on use of AI tools (LLM assistants, AI research and writing tools, prompt engineering) as part of your daily work — not just awareness, but active practice 

• Strong command of Agile methodology, backlog management, and cross-functional collaboration in a fast-paced, product-centric environment 

• Proven GTM and business acumen: experience with launch planning, data-driven solutioning, TAM/ICP analysis, and understanding cost and revenue drivers of software products 

• Experience in SaaS, credit management, or AR automation, with the ability to maintain current 
  delivery commitments while planning for future strategy 

The Role

We are looking for an elite engineer who builds like a hacker and communicates like a consultant. You will not just be building models in a notebook; you will be deployed to the front lines to build, architect, and ship end-to-end Agentic AI products directly for our most strategic customers.

This is a high-stakes role. You will face "tricky" customers who have vague requirements and high expectations. Your job is to translate their chaos into technical order, write production-grade code, and deploy autonomous agents that solve their actual business problems.

What You Will Do

• Build & Deploy (60%):

Design and ship full-stack AI applications. You own the pipeline from data ingestion to the LLM inference layer to the frontend interface.

Architect autonomous agentic workflows (using frameworks like LangChain, LangGraph, or custom implementations) that can reason, plan, and execute complex tasks.

Write robust, clean, and highly testable code (Python/Typescript). "It works on my machine" is not acceptable; it must work in the customer's restricted cloud environment.

Handle DevOps and MLOps constraints: Dockerizing agents, managing Kubernetes clusters, and optimizing inference latency.

• Customer Engineering (40%):

Serve as the technical face of the company for our most demanding accounts.

Navigate complex stakeholder environments. You will push back on unrealistic demands, clarify ambiguous requirements, and steer "tricky" customers toward technically feasible solutions without breaking rapport.

Translate technical constraints into business value for non-technical executives.

Generate high-quality data for our customers and ability to review the data generated by other experts. This is one of the most critical aspects of the role.

The "Must-Haves"

• Experience: 8–12 years of total engineering experience. You started as a strong Software Engineer and evolved into an AI specialist.
• Education: B.S./M.S. in Computer Science, Math, or Physics from a top-tier institution (IIT, MIT, Stanford, Harvard, Berkeley, CMU, or similar global top-ranking universities).
• Deep AI Fluency: You aren't just calling APIs. You understand RAG implementation nuances, vector database optimization, fine-tuning (LoRA/PEFT), and the architecture of agentic loops.
• Production Engineering: Experience with end-to-end deployment (AWS/GCP/Azure, CI/CD pipelines, Terraform, Docker).

The "Why You" (Soft Skills)

• Thick Skin & High EQ: You don't get flustered when a customer changes their mind for the third time in a week. You can hold your ground with a CTO and explain "why not" to a CEO.
• Extreme Attention to Detail: You catch the edge cases that others miss. You obsess over error handling, retry logic in agents, and data privacy.
• Grit: You enjoy the "messy" work of integrating legacy enterprise data just as much as prompting the latest model.

What will set you apart

• Public Code: A visible GitHub footprint is very helpful. We want to see your side projects, your contributions to open source, or your experiments with LLMs. Please include your GitHub link in your application.

Tech Stack

• Languages: Python (Expert).
• AI/Data (Expertise in all is not required): PyTorch, LangChain, LlamaIndex, Pinecone/Weaviate, OpenAI/Anthropic APIs, HuggingFace.
• Infra (Expertise in all is not required): Kubernetes, Terraform, AWS/GCP.

About the role: 

Turing is looking for people with LLM experience to join us in solving business problems for our Fortune 500 customers. You will be a key member of the Turing GenAI delivery organization and part of a GenAI project. You will be required to work with a team of other Turing engineers across different skill sets. In the past, the Turing GenAI delivery organization has implemented industry leading multi-agent LLM systems, RAG systems, and Open Source LLM deployments for major enterprises. 

Required skills

• 8 + years of professional, hands-on engineering experience, including 4–6+ years specializing in building and deploying AI/ML models and systems.
• 1+ year of experience in developing Generative AI (LLM) applications using techniques like prompt engineering, RAG, and/or agents.
• Expert in architecting GenAI applications/systems using various frameworks & cloud services
• Good proficiency in using various cloud services from Azure, GCP, or AWS for building the GenAI applications
• Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must.
• Experience in driving the engineering team toward a technical roadmap.
• Excellent communication skills to effectively collaborate with business SMEs

Roles & Responsibilities

• Build the technical roadmap given a business requirement and own the delivery of the same.
• Lead the engineering team toward a technical roadmap and ensure timely execution of the roadmap to achieve customer satisfaction. 
• Develop and optimize LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
• Codebase ownership: Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
• Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
• Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
• Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
• Continuous innovation: Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.

Education

• Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related technical field.

Strategic Project Lead / Delivery Manager 

Data Annotation & AI Delivery

8+ Years of Experience

Position Overview

We are looking for a seasoned Delivery Manager (8+ years of experience) to lead large-scale data annotation and curation projects in support of cutting-edge LLM and multimodal AI research. You will oversee end-to-end delivery for projects with 100+ team members, ensure world-class data quality, and drive process and tooling innovation in collaboration with AI researchers and cross-functional teams.

This role is ideal for someone who combines deep technical expertise, proven leadership in managing large teams, and a passion for advancing AI/ML innovation. Given that our key customers operate in the data analytics, data engineering, and Business Intelligence (BI) space, the ideal candidate will bring hands-on leadership experience with platforms such as Databricks and Snowflake, enabling them to deeply understand customer domains, speak their language, and deliver annotation outcomes that are contextually relevant and technically sound.

Primary Responsibilities

1. Team Leadership & Development

• Lead, mentor, and grow large-scale teams of annotators and trainers.
• Drive performance management, career development, and targeted training.
• Foster a culture of excellence, ownership, and continuous learning.
• Design and implement motivation strategies (including gamification) to boost engagement and reward top performers.

1. Project Management & Coordination

• Define and manage project scope, objectives, timelines, and quality metrics.
• Align with cross-functional stakeholders on goals and deliverables.
• Proactively identify and resolve delivery risks, blockers, and dependencies.
• Provide clear and consistent reporting on progress, challenges, and solutions.

1. Data Quality & Integrity

• Own quality control and data integrity across the annotation lifecycle.
• Analyze datasets to identify trends, anomalies, and insights for improvement.
• Implement best practices for annotation, evaluation, and data curation.
• Share learnings and continuously improve quality processes.

1. Technical Collaboration & Innovation

• Partner with engineering and research teams to optimize internal tooling.
• Stay ahead of emerging trends in AI, ML, and multimodal processing.
• Champion innovations that reduce task completion times and improve efficiency.
• Maintain clear and scalable documentation for processes and training.

1. Customer & Domain Engagement

• Serve as a domain-knowledgeable point of contact for customers operating in data engineering, analytics, and BI environments.
• Leverage hands-on experience with platforms like Databricks and Snowflake to understand customer data workflows, terminology, and quality expectations.
• Translate customer-specific data engineering and BI contexts into clear, actionable annotation guidelines and quality benchmarks for delivery teams.
• Collaborate with customers to define annotation taxonomies and evaluation criteria that align with their data pipeline and analytics use cases.

Required Skills & Qualifications

• 10+ years of experience in engineering, program management, or delivery of large-scale projects.
• Proven ability to lead and scale large teams (100+ members) with measurable impact.
• Strong technical grounding in AI/ML, data annotation, and multimodal systems.
• Hands-on leadership experience in data analytics, data engineering, or BI domains, with working knowledge of platforms such as Databricks and/or Snowflake (architecture, pipelines, data modeling, and production workflows).
• Familiarity with the modern data stack including ETL/ELT pipelines, data warehouses, data lakes, and BI tools (Power BI, Tableau, Looker, or similar).
• Ability to translate complex data engineering and analytics concepts into annotation frameworks, quality standards, and training materials.
• Proficiency in Python (preferred) or Swift for data analysis and automation.
• Strong mathematical and analytical skills for data-driven problem solving.
• Experience in data curation, annotation pipelines, and quality control.
• Excellent communication and stakeholder management skills.
• Track record of driving high-quality outputs under tight deadlines.

Preferred Skills & Qualifications

• Advanced degree in Computer Science, Data Science, AI, or related fields.
• Experience applying gamification to workforce engagement.
• Familiarity with modern project management tools & methodologies.
• Exposure to state-of-the-art multimodal AI technologies.
• Prior experience managing annotation or data labeling projects for customers in the data engineering, analytics, or BI space.
• Familiarity with SQL at an advanced level and data orchestration tools such as Apache Airflow, dbt, or Prefect.
• Certifications in Databricks (e.g., Data Engineer Associate) or Snowflake (e.g., SnowPro Core) are a plus.

Senior Data (Platform) Engineer 

Location: Hyderabad | Department: Technology, Data 

About the Role 

Are you passionate about building reliable, scalable data platforms that make analytics and AI development easier? As a Senior Data Platform Engineer, you will be hands-on in building, operating, and improving our core data platform and AI/LLM enablement tooling. 

You’ll focus on infrastructure, orchestration, CI/CD, and reusable frameworks that support analytics engineering and AI-driven use cases. You’ll work closely with Analytics Engineering and Insights teams and support other departments as they integrate with our data systems. 

What You'll Do 

Data Platform & Infrastructure

• Build, deploy, and operate cloud infrastructure for data and AI workloads using Infrastructure as Code (Terraform).
• Provision and manage cloud resources across development, staging, and production environments.
• Develop and maintain CI/CD pipelines for data transformations, orchestration workflows, and platform services.
• Operate and scale containerized workloads on Kubernetes, including Airflow, internal APIs, and AI/LLM services.
• Troubleshoot and resolve infrastructure, pipeline, and orchestration failures to ensure platform reliability.
• Maintain and support existing ML services and pipelines to ensure stability and reliability (No expectation to design or develop new ML models or training pipelines).
• Continuously monitor and optimize platform performance and cost. 

Framework, Tooling and Enablement

• Build and maintain reusable frameworks and patterns for dbt, Airflow, Cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks, etc.), Internal data and AI APIs
• Build and support infrastructure and pipelines for AI/LLM-based use cases, including orchestration, integration, and serving.
• Improve developer experience for Analytics Engineering and Insights teams by reducing friction in local development, deployments, and production workflows.
• Create and maintain technical documentation and examples to support self-service analytics and data development. 

What You’ll Need 

Technical Skills & Experience

• 5+ years of experience in data engineering, platform engineering, or similar hands-on roles.
• Strong programming skills in Python and SQL.
• Hands-on experience with:
  • Terraform
  • Airflow
  • dbt
  • Kubernetes
  • Cloud platforms (AWS, Google Cloud, or Microsoft Azure)
  • CI/CD pipelines (GitHub Actions, GitLab CI, CircleCI, etc.)
  • Cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks, etc.) 
• Strong understanding of analytical data models and how analytics teams consume data.
• Experience integrating and operating LLM-based pipelines and services (not model training). 

Soft Skills & Collaboration

• Strong problem-solving skills and ability to debug complex platform issues.
• Strong preference for declarative development, with the ability to clearly separate what a system should do from how it is implemented.
• Clear communicator who can work effectively with both technical and non-technical stakeholders.
• Pragmatic, ownership-driven mindset with a focus on reliability and simplicity. 

Why Join Us? 

We welcome people from all backgrounds who seek the opportunity to help build a future where we connect the dots for international property payments. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world of PropTech forward, together. 

Redpin, Currencies Direct and TorFX are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, colour, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.

About the Role

Workato is looking for a Principal Technical Architect, AI to join as a Field Specialist operating at the intersection of applied AI engineering and customer-facing technical strategy. This is a dual-mandate role with an approximately equal split:

Mandate 1 – AI Field Specialist (Customer-facing): You will work directly with enterprise customers and prospects in pre-sales and post-sales engagements to define and architect their AI strategies on Workato. This includes designing agentic automation solutions, advising on the latest approaches and best practices, scoping AI agent implementations, and helping customers move from proof-of-concept to production-grade autonomous systems.

Mandate 2 – Agentic CS Platform (Internal initiative): You will be a core architect and developer on Workato's autonomous Customer Success agent initiative, a production-grade system that captures complete customer context to support reasoning, and compounds intelligence over time. You will own the agent and memory architecture, evals and learning loop, and autonomy framework that power this system.

This is a role for someone who builds agentic systems to orchestrate LLMs into reliable, auditable, enterprise-grade agent architectures, and who can articulate that vision to a customer CIO and technical leaders as fluently as they can implement it in code.

Workato has a positive, diverse, and collaborative culture; we look for people who are curious, inventive, smart, hardworking, and who work to be a little better every day.

Responsibilities

AI Field Specialist

• Support as an expert AI architect in strategic enterprise engagements: roadmapping customer AI agent use cases and delivering technical deep-dives that demonstrate Workato's agentic capabilities.
• Lead architecture workshops with enterprise customers to define their AI automation strategy, including agent design, integration patterns, and governance frameworks.
• Advise customers on applied AI best practices: prompt engineering and agent orchestration patterns, evaluation and testing strategies for agent systems, confidence calibration, human-in-the-loop design, and continuous learning loops.
• Build reusable technical assets, such as reference architectures, solution blueprints, demonstration environments, and best-practice documentation, that enable the broader field team to position AI solutions.
• Develop and deliver technical collateral: architecture white papers, webinars, blog posts, conference talks, etc. that establish Workato's thought leadership in agentic automation.
• Partner with Product and Engineering to feed field insights back into the platform roadmap, ensuring customer-facing AI capabilities evolve based on real deployment patterns.
• Support global strategic accounts across the US, EMEA, and APAC geographies as needed for critical engagements.
• May require up to 20% global travel.

Agentic CS Platform

• Architect and implement core subsystems of the autonomous CS agent platform, including memory layers, the agent orchestration layer, and the decision trace architecture.
• Design and build a Customer Knowledge Graph as a structured, semantic network that models customers, users, policies, decisions, and operational artifacts as interconnected entities and relationships, enabling queryable representation of contextual states, and policy evaluations for governance, traceability, and decision optimization.
• Implement the confidence-based autonomy framework, including precedent matching, confidence scoring (precedent match, pattern recognition, data completeness, policy clarity), and policy-governed escalation routing.
• Define and design infrastructure architecture to ensure optimal performance and latency.
• Take scalable technology selection decisions.
• Establish evaluation frameworks: define metrics for decision quality, context accuracy, and learning velocity (autonomous threshold increases month over month).

Requirements

Qualifications & Experience

• B.Tech/BE or higher in Computer Science, Engineering, or related field. 
• 15+ years of total relevant experience in enterprise software architecture, design, and implementation.
• 8+ years of hands-on experience with Integration Platforms (MuleSoft, TIBCO, Oracle SOA, webMethods, or similar). Deep familiarity with iPaaS architecture patterns is essential.
• 2+ years of applied AI/Agents engineering experience, specifically in building systems that leverage LLMs and agent frameworks, orchestrating them into production applications.

Applied AI & Agent Architecture (Must-Have)

• Hands-on experience designing and building AI agent systems: multi-step reasoning pipelines, tool-use orchestration, and autonomous execution frameworks.
• Working knowledge of Python agent frameworks such as LangGraph, Claude Agent SDK, or equivalent. LangGraph experience with persisted state and human-in-the-loop patterns is strongly preferred.
• Experience with graph database design and implementation: entity modeling, relationship extraction, graph querying, and using graph structures for contextual retrieval. Neo4j/NetworkX equivalent experience is a plus.
• Practical experience with RAG architectures, vector databases, embedding strategies, and hybrid retrieval (vector + structured + graph).
• Understanding of evaluation and testing for AI systems: building evals, measuring agent quality, confidence calibration, A/B testing of prompts/pipelines, and regression testing for non-deterministic outputs.
• Familiarity with prompt engineering at production scale: structured prompting, chain-of-thought patterns, output parsing, retry/fallback strategies, and prompt versioning.
• Experience with observability for LLM systems: tracing, token/cost monitoring, and latency profiling. Familiarity with Langfuse, LangSmith, Phoenix, or similar tools.
• Experience with MCP (Model Context Protocol) standards for LLM-to-system integration.

Integration & Enterprise Architecture (Must-Have)

• Strong expertise in enterprise integration patterns: event-driven architectures, microservices orchestration, pub/sub messaging, and data synchronization.
• Deep working knowledge of APIs: RESTful, SOAP, webhooks, and data formats (JSON, XML).
• Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native services (Lambda/Functions, DynamoDB, Kafka/Kinesis, S3).
• Familiarity with enterprise applications: Salesforce, ServiceNow, SAP, Workday, NetSuite, or similar. Understanding how these systems participate in agentic workflows.
• Understanding of enterprise security and governance requirements: OAuth, SSO, data residency, SOX compliance, audit trails, and role-based access control.

Nice-to-Have

• Background in Customer Success platforms (Gainsight, ChurnZero) or CRM architecture.
• Prior experience in a customer-facing technical role (Solutions Architect, Field CTO, Technical Account Manager, or Pre-Sales Engineer) at a SaaS or platform company.
• Contributions to open-source AI/agent projects or published technical content in the applied AI space.

General Soft Skills

• Exceptional ability to communicate complex AI and architecture concepts to diverse audiences: from engineering teams to C-level executives: adapting depth and vocabulary to the room.
• Strong consultative instinct: able to listen to a customer's business problem, decompose it into architectural components, and propose a credible path forward in real-time.
• Entrepreneurial mindset with comfort operating in ambiguity: this role spans an internal build and an external advisory function, and requires someone who can context-switch and self-prioritize.
• Collaborative by default: able to work across Product, Engineering, Customer Success, Sales, and Marketing without needing formal authority.
• Excellent written communication: able to produce architecture documents, white papers, and technical briefs that are clear, precise, and persuasive.
• Fast learner who stays current with the rapidly evolving AI agent ecosystem and can distill emerging patterns into practical guidance.

(REQ ID: 2216)

Responsibilities

We are looking for an experienced and exceptional Senior AI Engineer (Voice AI) to join our growing team. In this role, you will be involved in the design, development, and optimization of AI and Machine Learning products that deliver exceptional user experiences. The ideal candidate will combine strong software engineering skills with deep knowledge of machine learning systems. If building AI products from zero to one that scales to serve millions of users from first principles of AI and engineering, you are at the right place. We are building organization-aligned agents that are consistent at scale from the ground up and looking for passionate builders who are rooted in foundational AI knowledge to reimagine the agent control and data plane.

As part of this role you will:

• Design and implement advanced AI/ML systems with a focus on SLMs, LLMs, AI Agents, and Search architectures.

• Build conversational AI interfaces that handle multi-turn low latency chat/voice customer interactions, maintain context across sessions, and seamlessly escalate to human agents when necessary.

• Build production-grade AI pipelines for data processing, model training, fine-tuning, benchmarking (dual-control, fluid model etc.) and serving at scale.

• Implement feedback loops and continuous learning systems that incorporate customer satisfaction metrics, agent corrections, LLM evaluations, human evaluations and conversation outcomes to improve model performance over time. Reinforce organizational policies based on knowledge bases, conversational data and memory systems.

• Create AI based analytics dashboards and reporting tools to track automation effectiveness, tracing for identifying bottlenecks, identify common customer pain points, and measure key performance indicators like resolution time, containment rate, and customer satisfaction scores. Quality assurance, management to get actionable insights from customer conversations and create evals for the current generation agents.

• Lead technical initiatives for AI system integration into existing products and services.

• Collaborate with data scientists and ML researchers to implement and productionize new AI approaches and models.

Requirements

Qualifications / Experience / Technical Skills

• Bachelor's degree in Computer Science, or a related field, or equivalent practical experience.

• 5+ years in backend software development using modern programming languages (e.g., Python (strongly preferred!), Golang or Java).

• Demonstrated experience building production AI systems including chatbots, virtual assistants, and automated support agents using SLMs, LLMs (commercial, open-source models).

• Demonstrated strong foundational understanding and appreciate first principles thinking in ML, NLP (transformer based models).

• Expertise in natural language understanding (NLU) and intent classification for customer query interpretation, entity extraction, dialogue state tracking and conversation flow management for building a reliable framework for context engineering.

• Expertise in tuning streaming ASR and TTS engines, Speech to Speech models for context and domain aware transcriptions and naturalness in voice.

• Expertise in conversation mining for identifying customer intents, root cause analysis, sentiment, resolution, policy adherence for not just auditing but truly understanding conversations for business outcomes across large enterprise scale.

• Expertise in working with use case based SLMs for realtime agent coaching and recommendations.

• Expertise in building knowledge bases and FAQ systems with dynamic content retrieval and self-learning capabilities from support interactions.

• Experience implementing multi-channel support automation across chat, email, voice, and messaging platforms with consistent context handling.

• Deep knowledge of REST API design, Pub-Sub architectures and integration patterns

• Experience working with PostgreSQL and ClickHouse, or similar relational and analytical databases (added advantage but not necessary skill)

• Strong understanding of software architecture, scalability, security, and system design.

• Experience with Docker, Kubernetes, and deploying to cloud environments (AWS, GCP, or Azure) is a plus

• Experience with A/B testing and experimentation frameworks.

Soft Skills / Personal Characteristics

• Strong communication abilities to explain technical concepts

• Collaborative mindset for cross-functional team work

• Detail-oriented with a strong focus on quality

• Self-motivated and able to work independently

• Passion for solving complex search problems

(REQ ID: 2676)

We are hiring across multiple locations

India: Hyderabad, Delhi NCR, Bengaluru
Europe: London, Serbia, Sofia, Lithuania, Berlin

About the role

Crunchyroll is growing and changing, presenting unique challenges and opportunities to support millions of anime fans around the world. The AI/ML team provides seamless help to our internal stakeholders, ensuring an exceptional experience for all Crunchyroll fans.

• Lead and mentor a team of data scientists focused on developing and deploying ML solutions including GNNs, LLM-based applications, and fraud detection models.
• Define and drive the roadmap for AI/ML initiatives across Crunchyroll’s product and platform ecosystem.
• Guide the development of robust ML pipelines and infrastructure, working closely with data engineering, software engineering, and DevOps teams.
• Establish best practices for experimentation, model evaluation, A/B testing, and continuous learning in production environments.
• Work with stakeholders across business, marketing, security, and content teams to identify AI opportunities and translate them into actionable projects.
• Ensure responsible AI/ML development by emphasizing model interpretability, performance, and fairness.
• Own operational metrics around model impact, latency, cost, and system scalability.
• Foster a strong team culture centered on innovation, curiosity, collaboration, and continuous learning.

About You

We get excited about candidates, like you, because...

• Bachelor's or Master's in Computer Science, Statistics, Data Science, or a related quantitative field.
• 8+ years of industry experience in data science or applied ML, with 4+ years of people leadership experience.
• Proven track record of delivering production ML systems that solve real-world business problems.
• Deep knowledge of ML/AI frameworks (e.g., PyTorch, TensorFlow, HuggingFace) and experience with applied NLP, GNNs, GraphRAG, and embeddings.
• Experience building systems leveraging Graph Databases, Vector Stores (e.g., FAISS, Pinecone), and cloud-native ML stacks (SageMaker, Databricks, etc.).
• Strong technical leadership, with the ability to direct teams to develop optimal ML solutions and guide research-to-production lifecycle.
• Excellent communication and stakeholder management skills; able to translate between business and technical worlds.
• A passion for building high-performing teams, mentoring others, and fostering a learning-first environment.

About the Team

The R&D team is dedicated to developing, testing, and validating robust and scalable machine learning models that drive business objectives. Our focus includes enhancing operational processes through AI/ML solutions, such as trend analysis, anomaly detection, and the deployment of large language models (LLMs) for tasks like querying system health. Another major focus area is preserving, and improving customer experience and retention. We closely work with our stakeholders to ensure AI/ML objectives are clearly defined.

About the role

Crunchyroll is growing and changing, presenting unique challenges and opportunities to support millions of anime fans around the world. The AI/ML team provides seamless help to our internal stakeholders, ensuring an exceptional experience for all Crunchyroll fans.

• Architect and implement end-to-end LLM-based applications, including chatbots, assistants, search agents, and knowledge discovery tools.
• Design and deploy scalable RAG and GraphRAG pipelines using vector databases (e.g., Opensearch, Pinecone, Mongo) and document chunking strategies.
• Fine-tune and optimize foundation models (e.g., Bedrock, Claude, Nova) for domain-specific use cases.
• Own prompt design and evaluation - build prompt libraries and frameworks that enable rapid experimentation and reuse.
• Develop APIs and microservices to serve LLM-based applications with real-time latency and uptime guarantees.
• Collaborate with data, platform, and backend teams to integrate LLM capabilities into broader Crunchyroll product experiences.
• Monitor and evaluate LLM systems in production for hallucination, latency, cost, and feedback loops.
• Stay up to date with the latest in LLM research, tooling (LangChain, LlamaIndex), and ecosystem advancements.

About You

We get excited about candidates, like you, because...

• Bachelor's or Master's degree in Computer Science, Machine Learning, AI, or a related field.
• 5+ years of experience building production ML/AI systems, with 2+ years specifically focused on LLM applications.
• Hands-on experience with production-ready RAG systems using tools like LangChain, LlamaIndex, or custom pipelines.
• Hands-on experience with GraphRAG, LLMs, Graph and Vector Databases.
• Deep understanding of prompt engineering, prompt templating, and prompt evaluation strategies.
• Experience working with major foundation models (OpenAI, Anthropic, Nova, Bedrock etc.).
• Familiarity with building semantic search systems and working with vector DBs at scale.
• Strong backend/API development experience using TypeScript and knowledge of deploying services to cloud environments.
• Python skills and experience working with AWS cloud platform and MLOps tools (e.g., AWS Bedrock, SageMaker, Databricks, Lambda, ECS/Fargate).

About the Team

The R&D team is dedicated to developing, testing, and validating robust and scalable machine learning models that drive business objectives. Our focus includes enhancing operational processes through AI/ML solutions, such as trend analysis, anomaly detection, and the deployment of large language models (LLMs) for tasks like querying system health. Another major focus area is preserving, and improving customer experience and retention. We closely work with our stakeholders to ensure AI/ML objectives are clearly defined.

As our DevOps Engineer, you will be required to: 

• Manage operational aspects of the Envoy Global Azure CI/CD pipeline including source control, build systems, infrastructure, networking, deployments, and permissions management
• Work closely with Development, Data, Project Management, and Infosec teams to ensure management, operability, and security of Envoy’s applications hosted in Azure.
• Participate in architecture, requirements, and planning sessions with project owners and stakeholders.
• Design and deliver DevOps projects that ensure infrastructure is 24x7 operational as well as cost effective.
• Train and mentor DevOps engineers to meet Envoy Global’s growing requirements for the future.
• Participate in planning sessions and daily stand-ups with multi-region DevOps staff
• Proactive planning and organization to adjust to the flexible needs of Envoy Global’s business.
• Ensure business continuity and disaster recovery plans are tested and updated on an annual basis.
• Serve as an escalation point to help prioritize and resolve complex or urgent issues and incidents.
• Maintain relationships with vendors and contractors for services and maintenance of software and systems.
• Ensure 24x7 5x9s uptime for Envoy Global applications.

To apply for this role, you should possess the following skills, experience and qualifications: 

• Expert, hands-on experience in application builds, deployments, and troubleshooting: specifically, but not limited to: .Net and SQL Server frameworks (msbuild, dotnet, ssdt, dacpac).
• Strong communication (written and verbal), analytical, organizational, and problem-solving skills. Must be able to present complex information to technical and non-technical stakeholders.
• Experience working with these technology areas:
  • Source control and CI/CD tools (Git, Azure DevOps, MSBuild, Jenkins, TeamCity, Octopus Deploy, Harness, etc.)
  • Azure platform services, including Azure SQL, Service Bus, Key Vault, Blob Storage
  • AI Technologies including Claude, OpenAI, MS Foundry, LLM, etc.
  • Kubernetes clusters (experience in Azure AKS a plus)
  • Infrastructure as Code tools such as Terraform and ARM/Bicep
  • Content Delivery/WAF providers (Cloudflare, Akamai, MS)
  • Monitoring tool sets such as DataDog, Splunk, ELK
• Self-motivated, self-directed, and customer service-focused with the ability to multi-task and manage competing priorities in a fast-paced environment
• Excellent critical thinking and troubleshooting skills.
• Champion Change and Release management
• Ability to expand knowledge and learn new technologies.
• Be available 24x7 to assist in releases as well as operational or security incidents.
• 3 - 6 years of DevOps experience with a focus builds and deployments, preferably in an Azure environment using infrastructure as a code deployment platforms (Git, Terraform, ARM, CloudFormation) and .net/agular builds and deployments using various tools including TeamCity, Git Runners, Octopus, Azure DevOps.
• Bachelor’s Degree in IT or related field
• Desired Certifications:  MCSE, ITIL, NIST, Azure Infrastructure/Architect (AZ-304,305,400,700).

About Us

Are you ready to build the future of supply chain? At Gather AI, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining “on-time, in full” delivery.

If you’re looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.

About the Team

You’ll work most closely with the fullstack engineering team and their leads, collaborating regularly with the cloud engineering team on API and backend testing, and with the ML team for feature validation. Cross-departmentally, you’ll work with Product Management on acceptance criteria and release readiness, and with Customer Support on field-reported issues.

About the Role

We are looking for a Senior QA Engineer to own the end-to-end test automation strategy for Gather AI’s fullstack platform. You will build and maintain Playwright-based E2E test suites, design API automation coverage, integrate tests into CI/CD pipelines, and develop a structured evaluation framework for LLM-powered features.

This is a greenfield opportunity to shape QA practices and tooling from the ground up at a production AI/robotics company — not a ticket-closing QA factory. Your work directly affects product quality for real customers.

What You’ll Do

• Build and maintain Playwright-based E2E test automation suites covering critical user workflows, API validation, and edge case handling across web applications
• Design and implement a comprehensive API automation framework for backend services, including REST endpoint coverage and data validation
• Integrate automated test suites into CI/CD pipelines (GitHub Actions) with reporting, failure alerting, and quality gates
• Develop a structured LLM tool evaluation framework — defining test methodologies, evaluation criteria, and repeatable benchmarks for AI/ML-powered features
• Identify and address gaps in test coverage, flaky tests, and QA technical debt; drive adoption of quality metrics (test coverage, defect escape rate, automation coverage)
• Collaborate with engineering leads, Product, and Customer Support to define release readiness criteria and prioritize regression coverage

What You’ll Need

• 5–8+ years of QA/test engineering experience with a strong focus on automation
• Hands-on Playwright experience building and maintaining E2E test suites (TypeScript/JavaScript)
• API test automation expertise using tools such as Playwright API testing, Postman/Newman, or pytest
• CI/CD integration experience (GitHub Actions, Jenkins, or similar) with test pipeline design and reporting
• BS in Computer Science, Engineering, or a related field; solid functional testing fundamentals and strong analytical thinking

Nice to Have

• Experience or aptitude for LLM/AI tool evaluation (prompt testing, output quality assessment, hallucination detection)
• Performance or load testing experience (k6, Locust, JMeter, or similar)
• Experience with database testing and data validation (SQL, data pipeline verification)
• Familiarity with Docker or containerized test environments

Software Engineer (AI Platforms)

About SingleStore

At SingleStore, we’re not just building a database company, we’re defining the future of data management. Going beyond multi-cloud, we offer customers flexible networking, storage, and compute options to meet their requirements. With a few clicks, our cloud service spins up production grade infrastructure using the latest capabilities of major cloud providers and the industry standard Kubernetes ecosystem.

As data systems evolve, the “database” is no longer just where queries run, it’s becoming the foundation for realtime AI applications: retrieval, reasoning, agent workflows, and intelligent automation over enterprise data. That’s the direction we’re building toward.

About the AI Platform Team

We build the software platform that powers AI native experiences across SingleStore: AI/ML capabilities, agent runtimes, tool integration, and the operational layer required to run these systems reliably at scale. Our work sits at the intersection of distributed systems, cloud infrastructure, and practical applied AI.

This team is not “pure research”, it’s engineering heavy. You’ll build product grade systems that let customers safely and reliably use AI on their data.

Role Summary

We are looking for a Software Engineer to design and implement core platform capabilities for AI/ML and AI Agents in SingleStore Cloud. You’ll work on services that enable model/tool orchestration (e.g.  MCP style tool discovery and execution), agent workflows, retrieval pipelines (embeddings/vector search), evaluation/observability, and secure multi tenant operations.

You will likely find yourself using Go and Python, Kubernetes, cloud primitives, and the right tools for the job,  while applying solid AI/ML fundamentals to make correct engineering decisions.

Role and Responsibilities

• Build and evolve backend services that power AI features: agent orchestration, tool execution, retrieval/RAG pipelines, and model serving integrations.
• Design APIs and control plane workflows for AI platform components (tenant-aware, secure by default, observable).
• Implement MCP style tool discovery / integration patterns so agents can safely call tools, connectors, and internal services.
• Work closely with product managers, designers, customers, and partner engineering teams to deliver high quality AI experiences.
• Engineer for reliability and scale: latency, cost controls, rate limiting, fallbacks, rollouts, and incident response readiness.
• Establish best practices around evaluation: offline test sets, regression detection, prompt/model/version tracking, and quality gates.
• Contribute to secure AI by design approaches: permissions, data access boundaries, prompt injection defenses, and auditability.
• Mentor junior engineers and contribute to a welcoming, high ownership team environment.

Required Skills and Experience

This is a software engineering role that requires strong fundamentals plus working knowledge of AI/ML concepts.

• Strong software engineering skills with experience in distributed systems (Go, Python, or similar).
• Experience building cloud native services: Kubernetes, containers, service-to-service APIs, CI/CD.
• 4+ years of experience working on a SaaS product or production platform.
• Solid understanding of AI/ML fundamentals (you don’t need to be a researcher, but you should understand concepts well enough to build correct systems):
• Supervised learning basics (training vs inference, overfitting, evaluation metrics, classification, anomaly detection, forecasting, regression etc.)
• LLM basics (tokens, context windows, prompting, tool/function calling concepts)
• Embeddings + vector search fundamentals (similarity, indexing tradeoffs, retrieval pitfalls)
• Strong debugging and problem-solving skills, including incident-style troubleshooting across services and infrastructure.
• Intellectual curiosity about investigating issues that impact product quality, reliability, latency, and business metrics.
• Passion for building robust, maintainable systems in a fast-paced, team-oriented environment.

Nice to Have (Preferred)

• Hands on experience with AI agents and orchestration frameworks (tool calling, workflows, planners/executors).
• Practical experience with RAG systems, reranking, grounding, and evaluation strategies.
• Experience with model serving patterns (batch/online inference, caching, streaming responses).
• Knowledge of security considerations for AI systems (data isolation, RBAC, prompt injection threats, audit logs).
• Familiarity with vector databases or vector capabilities in modern data platforms.
• Experience with observability stacks (structured logging, metrics, tracing) and SLO driven engineering.

Tech Stack

Go, Python, Kubernetes, cloud infrastructure, distributed systems, APIs, and modern AI tooling (LLM providers, embeddings, retrieval systems, eval/observability pipelines), ML tooling.

The job in short

Backbase just launched its new AI-powered Banking Platform globally. We are helping banks go from just experimenting with AI to actually using it to get things done. This platform automates key tasks and boosts productivity for both customer-facing and back-office teams, turning the potential of AI into real business results

We operate with a bold startup mindset prioritizing speed, autonomy, and breakthrough innovation.

As a System Engineer(DevOps) you’ll work in a team responsible for design, development and maintenance of the platform.

At each level of the architecture we apply industry standards ensuring stability, security and scalability while remaining cost efficient.

You should have experience in building and running platforms or infrastructures in production.

Considering the area of AI surrounding tools and frameworks are rapidly evolving, we are looking for engineers with a curious mindset and “doer” mentality.

If you have  passion in technology, eager to learn, adopt, deliver and work in short fast phased iterations - please go ahead and apply. 

How about you?

The ideal candidate will have a strong background in building and maintaining infrastructure using public cloud ( Azure, AWS, GCP), automation (python/golang), observability (prometheus/grafana),  infrastructure as code (IaC), identity and access management (IAM), security and DevOps practices.

This role requires familiarity with concepts of AI infrastructure and solutions offered by major players, emerging patterns of building GenAI products.

Preferred Qualifications:

Experience working with AI infrastructure is a big plus.
It’s not mandatory but let's have a chat  if you already have experience in of the following areas: 

• Experience with cloud based AI solutions: Azure Cloud Foundry/Amazon Bedrock 
• Observability and Security in AI  ( Langfuse)
• LLM Gateways ( LiteLLM) 
• Vector Databases
• Big bonus is experience with designing, deploying, maintaining MCP,  RAG, Agents

Required Qualifications:

Besides new and shiny AI/ LLM we believe that a strong proven background in engineering is essential. So if you yet don’t have experience with AI but have a good background in areas highlighted below. Please, do not hesitate and apply: 

• At least 5 years in a similar role running production  workloads on public cloud  ( Azure - preferred, AWS, GCP)
• Linux based OS, containerisation ( Docker, Containerd)  - configuration, optimisation,  monitoring, troubleshooting
• Kubernetes  ( Azure Kubernetes Service, Google Kubernetes Engine) - expert level 
• Observability - Prometheus, Grafana, Opentelemtry, concept of metrics
• Infrastructure as a Code, config management, GitOps - Terraform, Helm, ArgoCD
• Strong troubleshooting skills, experience with on-call 
• Automation and programming/scripting - python, golang
• Deep understanding of  infrastructure security 
• You have strong communication skills

Aisera is Global and our success draws upon the diverse viewpoints, skills and experiences of our employees. We are proud to be an equal opportunity employer and are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or veteran status.

#LI-SK1

Lookout, Inc. is a globally recognized cybersecurity leader delivering advanced protection for the most vulnerable element of any enterprise security strategy — human error and manipulation. Cloud-native by design, the Lookout platform offers rapid, scalable deployment and simplified security operations, defending the frontline of human-centric attacks—the mobile device. Attackers now target the human element more than ever, with mobile devices providing the most direct path to their victims. Using social engineering techniques that exploit basic human instincts like trust, curiosity, and urgency, they deceive users into revealing sensitive credentials, allowing them to slip past legacy security solutions.

Lookout Endpoint Detection and Response (EDR) continuously monitors mobile endpoints for signs of human-centric attacks, as well as traditional malware, software vulnerabilities, and other anomalous activity. It uses advanced threat detection techniques, including artificial intelligence (AI) and behavioral analysis, to identify threats before they escalate across the enterprise. Learn more at www.lookout.com and follow us on the Lookout Blog, LinkedIn, and X.

Lookout’s backend system supports a massive volume of data and an increasingly high level of demand, from data ingestion to delivery to dynamic analysis. We’re looking for talented and motivated engineers to build core components and services, as well as to contribute to evolving the architecture. We’re a small team working on a very large, modern system with a user base of millions, so you’ll get to work on a cutting-edge product and service on a large scale. We’re responsible for building and maintaining several of the services powering the various Lookout applications..

What you’ll do:

• You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
• Own the full machine learning lifecycle, from initial research and design to production deployment, monitoring, and continuous retraining.
• Establish and implement robust frameworks to train, evaluate, stress-test, and monitor ML/AI systems, driving continuous improvement and preventing model drift.
• Address and navigate real-world scale and performance challenges, ensuring all ML/AI models and systems are efficient, robust, and maintain target quality/latency under production constraints.
• Set technical direction as a senior Individual Contributor (IC) and mentor junior engineers.
• Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
• We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.

What we’re looking for: 

• BS/MS in Computer Science or related field/degree with at least  5-8 years of  work experience.
• A proven track record of architecting and deploying practical, high-impact ML/AI systems over multiple years, translating complex models into robust, real-world solutions.
• Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML/AI systems to life.
• Expert proficiency in Python and strong software engineering skills, including the ability to write reliable, production-grade code. In-depth experience with major ML/Deep Learning frameworks: PyTorch, TensorFlow, scikit-learn.
• Familiarity with modern AI/ML stacks like Hugging Face and LangChain.
• Deep expertise in a wide range of standard ML algorithms, including classification, clustering, regression, and deep learning models. 
• Hands-on experience with the LLM/RAG stack components: embeddings, knowledge graphs, vector databases, retrieval strategies, and prompt engineering. 
• Proven ability to measure and optimize model efficacy using statistical methods.
• Hands-on experience with production ML infrastructure, including feature stores, model management, training/serving pipelines (MLOps), and monitoring tools. 
• Up-to-date with new advances in NLP, LLMs and agent-frameworks.
• Strong grasp of software engineering fundamentals and algorithms.
• Experience with implementing secure, scalable API services.

Bonus Points:

• Practical experience applying advanced techniques to enhance model efficiency, including model distillation (creating smaller, faster student models) and model quantization (reducing memory footprint and latency).
• Experience with efficient Large Language Model (LLM) fine-tuning methods like LoRA and other PEFT techniques.
• Experience working with coding agents (Cursor, Copilot, Claude Code etc..)
• Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
• Professional programming experience with Scala and Golang
• Experience with serverless architectures on AWS, GCP.
• Experience with Kubernetes, container technology (Docker, ECS, EKS).

Lookout, Inc. is a globally recognized cybersecurity leader delivering advanced protection for the most vulnerable element of any enterprise security strategy — human error and manipulation. Cloud-native by design, the Lookout platform offers rapid, scalable deployment and simplified security operations, defending the frontline of human-centric attacks—the mobile device. Attackers now target the human element more than ever, with mobile devices providing the most direct path to their victims. Using social engineering techniques that exploit basic human instincts like trust, curiosity, and urgency, they deceive users into revealing sensitive credentials, allowing them to slip past legacy security solutions.

Lookout Endpoint Detection and Response (EDR) continuously monitors mobile endpoints for signs of human-centric attacks, as well as traditional malware, software vulnerabilities, and other anomalous activity. It uses advanced threat detection techniques, including artificial intelligence (AI) and behavioral analysis, to identify threats before they escalate across the enterprise. Learn more at www.lookout.com and follow us on the Lookout Blog, LinkedIn, and X.

Lookout’s backend system supports a massive volume of data and an increasingly high level of demand, from data ingestion to delivery to dynamic analysis. We’re looking for talented and motivated engineers to build core components and services, as well as to contribute to evolving the architecture. We’re a small team working on a very large, modern system with a user base of millions, so you’ll get to work on a cutting-edge product and service on a large scale. We’re responsible for building and maintaining several of the services powering the various Lookout applications..

What you’ll do:

• You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
• Own the full machine learning lifecycle, from initial research and design to production deployment, monitoring, and continuous retraining.
• Establish and implement robust frameworks to train, evaluate, stress-test, and monitor ML/AI systems, driving continuous improvement and preventing model drift.
• Address and navigate real-world scale and performance challenges, ensuring all ML/AI models and systems are efficient, robust, and maintain target quality/latency under production constraints.
• Set technical direction as a senior Individual Contributor (IC) and mentor junior engineers.
• Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
• We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.

What we’re looking for: 

• BS/MS in Computer Science or related field/degree with at least  5-8 years of  work experience.
• A proven track record of architecting and deploying practical, high-impact ML/AI systems over multiple years, translating complex models into robust, real-world solutions.
• Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML/AI systems to life.
• Expert proficiency in Python and strong software engineering skills, including the ability to write reliable, production-grade code. In-depth experience with major ML/Deep Learning frameworks: PyTorch, TensorFlow, scikit-learn.
• Familiarity with modern AI/ML stacks like Hugging Face and LangChain.
• Deep expertise in a wide range of standard ML algorithms, including classification, clustering, regression, and deep learning models. 
• Hands-on experience with the LLM/RAG stack components: embeddings, knowledge graphs, vector databases, retrieval strategies, and prompt engineering. 
• Proven ability to measure and optimize model efficacy using statistical methods.
• Hands-on experience with production ML infrastructure, including feature stores, model management, training/serving pipelines (MLOps), and monitoring tools. 
• Up-to-date with new advances in NLP, LLMs and agent-frameworks.
• Strong grasp of software engineering fundamentals and algorithms.
• Experience with implementing secure, scalable API services.

Bonus Points:

• Practical experience applying advanced techniques to enhance model efficiency, including model distillation (creating smaller, faster student models) and model quantization (reducing memory footprint and latency).
• Experience with efficient Large Language Model (LLM) fine-tuning methods like LoRA and other PEFT techniques.
• Experience working with coding agents (Cursor, Copilot, Claude Code etc..)
• Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
• Professional programming experience with Scala and Golang
• Experience with serverless architectures on AWS, GCP.
• Experience with Kubernetes, container technology (Docker, ECS, EKS).