Agentic AI Lab Automation Engineer

Lilly; San Francisco (CA); On-site; USD 69,000 - 196,000; Full time

Job summary

Lilly is seeking a skilled engineer to advance Frontier AI by building autonomous agent systems that connect AI planning with real lab instruments. You will prototype, productionize, and collaborate with chemists, biologists, and automation engineers to accelerate discovery.

The role emphasizes hands-on development, integration, and deployment of scalable Python applications within cloud and lab environments, including container orchestration and data pipelines.

Qualifications

• MS + 1 year or BS + 3 years in Computer Science, Engineering, or related field with wet-lab automation experience.
• Demonstrated experience with lab automation systems and LIMS/ELN integration.
• Direct experience integrating software control and/or AI systems with lab automation platforms (liquid handlers, analytical instruments, robotic workflows).

Responsibilities

• Build multi-agent systems with robust orchestration, state management, error recovery, and tool integration.
• Prototype and iterate on agent planning, memory, and human-in-the-loop patterns.
• Design agent architectures that interface with lab automation platforms for closed-loop experimental execution.
• Partner with engineers and scientists to transition prototypes into reliable lab operations.
• Deploy containerized services using Docker and Kubernetes with GitOps/CI/CD.

Skills

Agentic AI

Lab automation

Python programming

Workflow orchestration

OpenVIP/CI tooling

Education

MS + 1 yr or BS + 3 yrs in CS/Engineering/Math

Tools

Docker

Kubernetes

LangChain/LangGraph

OpenTelemetry

Job description

Lilly is seeking a skilled engineer to advance Frontier AI by building autonomous agent systems that connect AI planning with real lab instruments. You will prototype, productionize, and collaborate with chemists, biologists, and automation engineers to accelerate discovery.

The role emphasizes hands-on development, integration, and deployment of scalable Python applications within cloud and lab environments, including container orchestration and data pipelines.