AI Solution Architect - MQ DIA
lilly · India, Bangalore ·
- Category
- Architecture
- Experience
- 3+ years
lilly · India, Bangalore ·
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 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 flows.
Preferred
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 Professional.
At 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.
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form () for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
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