AI Lead - Applied AI & Agentic Systems

Company Description

Star Health and Allied Insurance Co. Ltd. is a leading Indian health insurance company headquartered in Chennai and recognized as the country’s first standalone health insurance provider since 2006. The company offers a wide range of innovative products across health, personal accident, and overseas and domestic travel insurance to meet diverse customer needs. With more than 16.9 crore lives covered and a strong presence through 800+ branch offices, 14,000+ employees, and 5.8 lakh agents, Star Health operates at significant scale across India. The organization focuses on fast, in-house claim settlement, extensive cashless treatment through 14,000+ network hospitals, and strong bancassurance and digital channels. Star Health emphasizes customer experience through 24x7 multilingual support, free telehealth consultations, and ongoing digital transformation to ensure quality service, ease of access, and a seamless user experience.

YOUR MISSION: Translate business vision into an enterprise AI roadmap and lead teams to build reliable ML, GenAI and agentic products that create measurable insurance outcomes.

What you'll own

• Shape the AI roadmap. Partner with HODs, CXOs and their -1 leaders to identify opportunities, prioritise use cases and translate strategic goals into an executable AI portfolio.
• Architect AI products. Design end-to-end ML, GenAI and agentic solutions across models, RAG, tools, APIs, state, orchestration, human approvals, security and observability.
• Lead agentic delivery. Guide hands-on implementation using LangGraph, CrewAI or similar frameworks; define routing, specialist agents, memory/state, tool permissions, retries and loop controls.
• Drive productionisation. Move priority use cases from discovery to production with evaluation, MLOps/LLMOps, monitoring, fallbacks, cost controls, governance and adoption.
• Lead the team. Set technical direction, review designs and model choices, mentor AI talent and create strong ownership for quality, velocity and measurable outcomes.
• Build across teams. Work with Data, Product, Engineering, Architecture and Business teams to create reusable AI components and remove delivery dependencies.

What you'll bring

• Hands-on experience. 7-10 years in ML/DL or applied AI, including 3+ years implementing GenAI solutions in production.
• Framework depth. Hands-on LangGraph, CrewAI or comparable agent orchestration experience; strong LangChain or similar LLM application framework experience.
• AI/ML depth. Strong ML/DL foundations plus RAG, embeddings, vector search, reranking, model routing, multimodal AI, optimisation and evaluation.
• Strong engineering. Python, APIs/FastAPI, async services, cloud, Git, Docker, CI/CD and practical MLOps/LLMOps; product engineering experience preferred.
• Leadership judgement. Engage CXOs/HODs, simplify complex trade-offs, manage teams and balance business value, architecture, risk, latency and cost.

What will make you stand out

• Builder + architect. Show systems you helped build end-to-end - from an ambiguous business problem through architecture, implementation, production and adoption.
• Agent depth. Open and debug the graph: state, routing, tools, hand-offs, retries, checkpoints, human approvals, traces and failure paths.
• Ownership under ambiguity. Be self-starting, comfortable with leap goals and able to turn loosely defined leadership intent into measurable execution.

Why this opportunity stands out

• Enterprise-wide canvas. Build AI across sales, onboarding, underwriting, claims, FWA, service, operations, technology and employee productivity.
• Direct leadership exposure. Work with business leaders to shape where AI should change journeys, decisions and operating models.
• Own the full loop. Lead from problem discovery and roadmap through architecture, delivery, production adoption and impact measurement.
• Shape the AI platform. Define reusable agents, RAG patterns, evaluation standards, engineering guardrails and ways of working for Enterprise AI.