We are seeking a Lead Product Development AI Engineer – Full Stack who can drive end-to-end product delivery while architecting and operating GenAI, agentic AI and MCP capabilities in production. This role is hands-on: you will build customer-facing features across frontend and backend, lead discovery and design, define non-functional requirements, and ensure AI integrations are safe, reliable, measurable, and cost-effective.
About You – experience, education, skills, and accomplishments
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Bachelor’s degree in engineering or master’s degree (BE, ME, B Tech, MTech, MCA, MS)
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Minimum 7+ years of professional experience
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Solid development experience in a commercial IT environment
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Passionate about code and software architecture
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Strong web-focussed development skills
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Effective communicator at all levels, excellent inter-personal skills, strong business focus
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Highly self-motivated, confident to work on projects alone as well as in a team
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An enthusiastic approach to extending knowledge and learning new skills
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Strong commitment to quality of work and a good attention to detail
Expert in
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Java 11/17, Spring Boot (REST APIs, microservices)
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Microservices architecture (API contracts, versioning, service decomposition)
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Angular 18+, NodeJS (micro frontends)
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Scalable system design (event-driven, distributed systems)
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Non-functional architecture (latency, security, observability)
Must have experience in
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End-to-end product delivery (UI–API–data–production support)
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Software design patterns
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AI integration (Azure OpenAI/OpenAI APIs)
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RAG pipelines (chunking, embeddings, retrieval orchestration)
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Prompt engineering (few-shot, structured outputs, guardrails)
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AI assistants & agents (tool calling, workflows, memory patterns)
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AI evaluation (Ragas, prompt testing, regression evaluation)
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Production readiness (monitoring, alerting, incident response)
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Debugging distributed systems (logs, tracing, root cause analysis)
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Working with continuous integration environments
It would be great if you also had
- CI/CD pipelines (GitHub Actions, Jenkins, Azure DevOps)
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Vector databases (Azure AI Search, Pinecone, Weaviate, FAISS)
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Responsible AI (prompt injection defense, PII masking, policy enforcement)
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Experimentation (A/B testing, feature flags – Split.io)
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Platform thinking (shared AI services, reusable components)
What will you be doing in this role?
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Product Development
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Lead technical design of features; partner with Product, BA, UX and architects to derive solution architecture, technical specifications, and delivery plans.
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Define and document non-functional requirements (latency, availability, security, scalability, observability) and ensure features meet agreed targets.
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Design and build microservices and RESTful APIs using Java 11/17 and Spring Boot; apply clean architecture principles, API versioning, backward compatibility, and secure-by-default patterns.
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Lead frontend architecture and develop in Angular 18+ including state management, modular design, performance optimization, accessibility, and consistent UX patterns.
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Drive engineering excellence: code reviews, operational readiness (logging, metrics, tracing, alerting).
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Own end-to-end delivery for assigned epics—from design through implementation, rollout, monitoring, and iterative improvements—while proactively managing risks and dependencies.
AI Development
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Implement AI integrations, including RAG patterns, embeddings, prompt orchestration, and prompt safety/guardrails.
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Build AI assistants and agent-based workflows embedded into product experiences, including tool/function calling, multi-step reasoning flows, and user feedback loops.
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Write and maintain high-quality prompts and system instructions; apply prompt engineering best practices, structured outputs, and robust error handling.
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Design retrieval pipelines: chunking strategies, embedding selection, indexing approaches, and relevance tuning; choose and integrate vector databases as appropriate.
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Establish evaluation (AI eval) practices: define success metrics, build offline/online evaluation datasets, implement regression tests, and monitor quality drift in production.
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Ensure responsible AI practices: data privacy, PII handling, prompt injection mitigation, content safety, and secure integration of model endpoints.
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Optimize AI feature performance with respect to latency and cost, batching, streaming responses, fallback strategies, and graceful degradation.
Collaboration
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Mentor and guide engineers on full-stack and AI integration patterns; raise overall engineering standards through examples and coaching.
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Communicate trade-offs clearly to stakeholders; drive alignment on scope, milestones, quality bars, and risk mitigation.
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Contribute to technical roadmap and platform improvements (developer experience, shared libraries, observability, security posture).
Product you will be developing
Our team develop the product Cortellis and we develop features and enhancements on Cortellis umbrella of products like CCI, CDI, CTI and CRI
About the Team
Cortellis is Clarivate’s flagship product in Life Sciences domain. Cortellis customers include top 50 global pharmaceutical companies, amongst many others. The technology team for Cortellis sits out of Bengaluru and consists of four different squads that work on development of new features using latest technologies. Our tech stack includes Angular, NodeJS, Java, Spring Boot, Oracle, Postgres, Elastic Search, Coherence etc. We use microservices architecture and cloud-native tools/technologies that include EC2, S3, SQS etc.
Hours of Work
Full-time contract (9 hours per day, including 1 hour break, IST hours)
At Clarivate, we are committed to providing equal employment opportunities for all qualified persons with respect to hiring, compensation, promotion, training, and other terms, conditions, and privileges of employment. We comply with applicable laws and regulations governing non-discrimination in all locations.
