Agentic Automation Lead: AI-Driven Lab Platform

100 Eli Lilly and Company; South San Francisco (CA); On-site; USD 194,000 - 339,000; Full time

Benefits offered by this job

401(k) plan

Pension

Medical, dental, vision

Job summary

Lilly is seeking an experienced Automation AI Scientist to design and build agentic systems that plan, execute, and learn from physical experiments. You will own the decision layer of the closed-loop lab, guiding experiments, and updating strategies with scientists in the loop.

This on-site role leads a small team of scientist-engineers, pairs with chemists and automation engineers, and uses Docker/Kubernetes with CI/CD to deliver a production-grade platform.

Qualifications

• PhD (or MS + 3 yrs / BS + 6 yrs equivalent) in Computer Science, Chemical Engineering, Robotics, Chemistry, Computational Biology, or a related discipline.
• 5+ years of applied experience building AI or algorithmic decision systems, including production LLM agent or multi-agent systems.
• At least one year of direct people management experience.

Responsibilities

• Design and build agentic systems for planning experiments and data collection.
• Lead the development of multi-agent orchestration with robust state management and error recovery.
• Bridge high-level scientific intent to instrument control across Hamilton, Tecan, Opentrons, LC/MS, NMR, HPLC.
• Implement active learning, Bayesian optimization, and RL for autonomous experiment selection.
• Instrument the loop so each experiment produces model-ready data in ELN/LIMS.
• Deploy and maintain containerized services using Docker and Kubernetes with GitOps/CI/CD.
• Lead and grow a small team of scientist-engineers and own the platform end-to-end.

Skills

AI systems

Team leadership

Lab automation

Education

PhD or MS/BS with experience

Job description

Lilly is seeking an experienced Automation AI Scientist to design and build agentic systems that plan, execute, and learn from physical experiments. You will own the decision layer of the closed-loop lab, guiding experiments, and updating strategies with scientists in the loop.

This on-site role leads a small team of scientist-engineers, pairs with chemists and automation engineers, and uses Docker/Kubernetes with CI/CD to deliver a production-grade platform.