AI Solution Architect - MQ DIA

Job description

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 Technology@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 Business Function: Eli Lilly's Global DIA organization is seeking an AI Solution Architect / Lead to own the end-to-end AI and analytics architecture across the Manufacturing & Quality (MQ) technology portfolio. This is a strategic, hands-on leadership role for a senior technologist with deep roots in pharmaceutical manufacturing, enterprise AI platforms, and GxP-regulated system design. The architect will set technical direction, govern AI solution quality, and bridge business strategy to production-grade intelligent systems across quality management, manufacturing line analytics, pharmacovigilance, and the Global Manufacturing Data Fabric. Role: AI Solution Architect / Lead  Key Responsibilities AI Architecture & Technical Leadership • Define and own the AI/analytics solution architecture across the MQ DIA portfolio — covering data ingestion, RAG pipelines, agentic orchestration, MCP server ecosystems, model serving, and GxP-compliant deployment. • Lead Architecture Review Boards (ARBs), produce Architecture Decision Records (ADRs), and enforce design standards across squads and platforms. • Evaluate and select AI/ML frameworks, cloud services, and data platforms — maintaining a technology radar aligned to Lilly's enterprise direction. • Translate executive strategy into multi-quarter technical roadmaps with phased deliverables, resource estimates, and risk registers. Agentic AI, RAG & Advanced Analytics • Architect multi-agent orchestration systems (LangGraph, AutoGen, CrewAI) for manufacturing workflows: deviation investigation, complaint triage, CAPA recommendation, and batch release support. • Design enterprise RAG architectures across QMS, MES, and regulatory knowledge bases with retrieval fidelity, hybrid search, and audit-ready provenance. • Define MCP server architecture standards for exposing manufacturing APIs (Veeva, MES, LIMS) as structured LLM-consumable tool interfaces. • Architect real-time analytics on OSI PI / Kafka streams for predictive quality, OEE optimization, and process excursion detection. Cloud & Data Platform • Own cloud architecture strategy across AWS, Azure, and Databricks — ensuring security posture, GxP compliance, and cost governance. • Design the data lake integration layer: medallion architecture (Bronze/Silver/Gold), data contracts, schema registries, and lineage governance on Delta Lake. • Define MLOps architecture: model registry (MLflow), drift detection, retraining pipelines, and model lifecycle governance. • Govern MuleSoft + MCP integration patterns — clean separation between legacy integration investments and new AI tooling layers. GxP Compliance & AI Governance • Serve as AI governance authority: model explainability, audit trails, human-in-the-loop gates, and regulatory defensibility of AI-assisted decisions. • Lead CSV framework design for AI/ML systems under 21 CFR Part 11, EU Annex 11, and GAMP 5 — including IQ/OQ/PQ templates and risk-based validation strategies. • Engage Global QA, Regulatory Affairs, and IT Risk to qualify new AI capabilities for GxP manufacturing environments. Team Development & Stakeholder Leadership • Mentor distributed AI engineering and platform architecture teams; define engineering standards and review processes. • Represent MQ DIA in enterprise AI governance forums, architecture councils, and with executive stakeholders across Manufacturing, Quality, and Regulatory. • Partner with HR to define hiring profiles and skill frameworks for the MQ AI engineering community. Qualifications Required • Bachelor's in Computer Science, Engineering, Data Science, or related