CTI MD Tech@Lilly – Senior Data Architect – AI & Agentic Solutions
Eli Lilly
- Location
- Bangalore, Karnātaka, India
- Employment
- Full Time
- Work model
- On-Site
- Level
- Senior
- Posted
- Sep 1, 2026
Skills
About this role
At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us. About Lilly At Lilly, everything we do starts with patients. We unite caring with discovery to make life better for people around the world. Headquartered in Indianapolis, Indiana, our global team of over 50,000 employees work with urgency and purpose to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. We bring our best to this work because people depend on it. If you're driven by purpose and determined to make a meaningful difference for patients, we invite you to bring your skill and your commitment to Lilly. About Tech@Lilly At Lilly, technology is not a support function. It is how a global medicine company operates, innovates, and delivers. Lilly in Bengaluru builds the capabilities that make this possible — cloud platforms, AI systems, and automation at enterprise scale — all in service of a purpose that makes this technology work genuinely distinctive, from advancing drug discovery to enabling connected clinical trials to keeping a global medicine company running at the standard patients deserve. About the Organization The Clinical & Non-Clinical Data Organization at Eli Lilly and Company is responsible for the design, build, and operation of enterprise data platforms that power drug discovery, clinical development, and regulatory submissions. Data Hub is building a robust Data Strategy to make Lilly's Clinical and Non-Clinical data AI-ready and audit-ready, delivering scalable, governed, and reusable data products that accelerate how medicines reach patients. The data engineering organization sits at the intersection of science, technology, and patient impact — connecting Clinical and Non-Clinical data across the full chain, from ingestion to consumption. Path/Level: R5 (Senior Data Architect) Position Summary The Senior Data Architect (R5) is a hands-on leader who designs and personally builds AI and agentic solutions that operate at enterprise scale across Lilly's Clinical and Non-Clinical data domain — multi-agent systems, LLM-orchestrated pipelines, and retrieval/reasoning architectures built on governed, semantic data foundations. This is a builder role: the architect writes code, stands up agent frameworks, and ships production AI systems personally, not just specifications. This role is split 70% hands-on technical execution including coding and 30% strategy, and shapes the future technology landscape. A defining mandate of this role is Right Model, Right Task — routing every agentic and LLM workload to the model best suited to it on cost, latency, and accuracy grounds, integrated directly with Lilly's internal data platform so routing and reasoning are grounded in enterprise-native lineage and knowledge graphs rather than bespoke, disconnected metadata. Agentic and AI-assisted ways of working are the expected default across every design, analysis, and documentation activity — and this leader is the reference point for how the broader India team scales AI-native architecture.
Key Responsibilities
AI & Agentic Solution Architecture (Hands-On) Architect and personally build multi-agent and LLM-orchestrated solutions — planning/tool-calling agents, retrieval-augmented generation (RAG), and agent-to-agent workflows — for Clinical and Non-Clinical use cases. Design for