AI Solution Architect - MQ DIA
Eli Lilly and Company9 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Own AI and analytics solution architecture across the Manufacturing & Quality DIA portfolio, including data ingestion, RAG pipelines, agentic orchestration, MCP servers, model serving, and GxP-compliant deployment.
- Lead Architecture Review Boards, create Architecture Decision Records, establish design standards, and maintain technology-selection and enterprise-alignment practices.
- Architect multi-agent manufacturing workflows for deviation investigation, complaint triage, CAPA recommendation, and batch release support.
- Design enterprise RAG across QMS, MES, and regulatory knowledge bases with hybrid search, retrieval fidelity, and audit-ready provenance.
- Define MCP server standards for exposing Veeva, MES, and LIMS APIs as LLM-consumable tools.
- Design real-time analytics using OSI PI and Kafka streams for predictive quality, OEE optimization, and process-excursion detection.
- Own AWS, Azure, and Databricks cloud architecture, including security posture, GxP compliance, cost governance, data-lake integration, Delta Lake governance, and MLOps architecture.
- Lead AI governance and CSV framework design, including explainability, audit trails, human-in-the-loop controls, IQ/OQ/PQ templates, and risk-based validation.
- Mentor distributed AI engineering and platform architecture teams and represent MQ DIA in governance forums, architecture councils, and executive discussions.
- Partner with HR to define hiring profiles and skill frameworks for the MQ AI engineering community.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; a Master’s or PhD is preferred.
- 10–15 years of experience in AI/ML systems, solution architecture, and enterprise data platforms, including at least 5 years as a principal or lead architect.
- At least 3 years of experience in pharmaceutical, biotech, or regulated manufacturing with GxP or 21 CFR Part 11 exposure.
- Expertise in RAG, agentic orchestration, MCP, embeddings, and prompt engineering in production environments.
- Advanced proficiency with AWS services including SageMaker, Bedrock, EKS, and Redshift; Azure services including Azure OpenAI, Azure ML, and Synapse; and Databricks technologies including Delta Lake, MLflow, and Mosaic AI.
- Strong knowledge of ISA-95/88 manufacturing standards, pharmaceutical QMS concepts such as CAPA, OOS, and batch disposition, and pharmacovigilance data flows.
- Preferred experience with Veeva QMS, QBDVision, OSI PI, MES platforms such as Tulip or Werum PAS-X, LabVantage, or STARLIMS.
- Familiarity with AI Gateway, Lakehouse/Databricks environments, MuleSoft integration architecture, FDA AI/ML-based SaMD guidance, ICH Q8–Q10, data mesh, and ontology engineering.
- Preferred certifications include AWS Solutions Architect Pro, Azure Solutions Architect Expert, and Databricks ML Professional.
Benefits
- Lilly describes a supportive and respectful work environment intended to give employees space to do their best work.
- Workplace accommodations are available for individuals with disabilities during the application process.
Tech Stack
Categories
About Eli Lilly and Company
Eli Lilly and Company researches, develops, manufactures, and markets prescription medicines and biologics for patients, sold through healthcare providers, pharmacies, and payers. Core therapeutic areas include diabetes, oncology, immunology, neuroscience, and obesity. Founded in 1876 and headquartered in Indianapolis, it is a public company (NYSE: LLY) with global operations and is building a new advanced manufacturing site for gene therapy and other modalities in Lebanon, Indiana.