Eli Lilly - AI Solution Lead Architect in Bangalore, भारत

AI Solution Architect / LeadAbout 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 https://jobeax.com/link/aPR7qRrt9dPU9HxY 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 https://jobeax.com/link/77OFSM240Lz8sBVo 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 https://jobeax.com/link/cN0QEcqhX5BezhQu 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 https://jobeax.com/link/pOXXL9aKZGQ1Sfws 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 https://jobeax.com/link/m5d0i0XyL4iiQiIP & 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 https://jobeax.com/link/a9VAVFPzAz7r6yzT 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 https://jobeax.com/link/80kha56JFBU19uso 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 https://jobeax.com/link/FmeIXUHrkmWTFPA5 Required :- Bachelor's in Computer Science, Engineering, Data Science, or related field; Master's / PhD preferred.- 10 - 15 years in AI/ML systems, solution architecture, and enterprise data platforms - minimum 5 years as principal/lead architect.- 3 years in pharmaceutical, biotech, or regulated manufacturing with GxP / 21 CFR Part 11 exposure.- Expert command of RAG, agentic orchestration, MCP, embeddings, and prompt engineering in production environments.- Advanced proficiency in AWS (SageMaker, Bedrock, EKS, Redshift), Azure (Azure OpenAI, Azure ML, Synapse), and Databricks (Delta Lake, MLflow, Mosaic AI).- Strong knowledge of ISA-95/88 manufacturing standards, pharmaceutical QMS concepts (CAPA, OOS, batch disposition), and pharmacovigilance data https://jobeax.com/link/0yHlFSsCX7mzVTOB :- Hands-on experience with Veeva QMS, QBDVision, OSI PI, MES (Tulip, Werum PAS-X), or LabVantage / STARLIMS.- Familiarity with AI Gateway platform, Lakehouse/Databricks environment, or MuleSoft integration architecture.- Knowledge of FDA AI/ML-based SaMD guidance, ICH Q8-Q10, and data mesh / ontology engineering.- Certifications: AWS Solutions Architect Pro, Azure Solutions Architect Expert, Databricks ML https://jobeax.com/link/QluZMJ5Yvv8B8XO1 Lilly, caring is not only what we do for patients. It is how we work. We believe the people who dedicate themselves to making medicines better deserve an environment that makes their lives better too, one where they are supported, respected, and given the space to do their best work. This is not just a policy. It is who we are. (ref:hirist.tech)