Sr. Principal or Engineering Advisor - Agentic Lab Automation Integration
Eli Lilly and Company
August 24, 2026
Remote friendly (South San Francisco, CA)
United States
$132,000 - $222,200 USD yearly
IT
Position Summary
- Engineer integrations between agentic AI and physical lab systems, connecting robotic platforms, analytical instruments, and data pipelines.
- Design agent workflows to reason over experimental data, trigger automated actions, and surface insights to scientists.
- Prototype rapidly, productionize what works, and collaborate with chemists, biologists, and automation engineers.
Research & Innovation
- Build multi-agent systems with orchestration, state management, error recovery, and tool integration.
- Prototype and iterate on agent planning, memory systems, and human-in-the-loop patterns.
- Interface agent architectures with lab automation platforms (Hamilton, Tecan, Opentrons) for closed-loop execution.
Solution Deployment
- Transition prototypes into reliable lab operations with automation engineers and scientists.
- Deploy and maintain containerized services (Docker, Kubernetes) using GitOps and CI/CD.
- Integrate orchestration frameworks (e.g., Argo on Kubernetes) with laboratory control systems.
External Engagement
- Publish, give talks, review papers, and scout emerging trends in AI@Lilly/external community.
- Evaluate vendors, open-source projects, and academic collaborations.
Basic Qualifications
- PhD (or MS + 2 yrs / BS + 5 yrs) in Chemical/Mechanical Engineering, Robotics, Computer Engineering, or related field; demonstrated wet-lab automation.
- Experience with lab automation systems and LIMS engineering.
- Experience integrating software/AI with lab automation (liquid handlers, analytical instruments, robotic workflows).
- Strong Docker + Kubernetes production orchestration.
- Scalable production Python apps (e.g., Redis, FastAPI, Flask/Streamlit, pytest).
Preferred
- LLM post-training/fine-tuning/RLHF; AI integrated with lab automation.
- Ability to build the translation layer from planning logic to instrument control.
- Research experience with ML/NLP publications (e.g., NeurIPS/ICML/ICLR/ACL).
Compensation/Benefits
- Anticipated wage: $87,000–$222,200; eligible for company bonus and comprehensive benefits (401(k), medical/dental/vision, vacation, life insurance, time off/leave, well-being programs).
- Engineer integrations between agentic AI and physical lab systems, connecting robotic platforms, analytical instruments, and data pipelines.
- Design agent workflows to reason over experimental data, trigger automated actions, and surface insights to scientists.
- Prototype rapidly, productionize what works, and collaborate with chemists, biologists, and automation engineers.
Research & Innovation
- Build multi-agent systems with orchestration, state management, error recovery, and tool integration.
- Prototype and iterate on agent planning, memory systems, and human-in-the-loop patterns.
- Interface agent architectures with lab automation platforms (Hamilton, Tecan, Opentrons) for closed-loop execution.
Solution Deployment
- Transition prototypes into reliable lab operations with automation engineers and scientists.
- Deploy and maintain containerized services (Docker, Kubernetes) using GitOps and CI/CD.
- Integrate orchestration frameworks (e.g., Argo on Kubernetes) with laboratory control systems.
External Engagement
- Publish, give talks, review papers, and scout emerging trends in AI@Lilly/external community.
- Evaluate vendors, open-source projects, and academic collaborations.
Basic Qualifications
- PhD (or MS + 2 yrs / BS + 5 yrs) in Chemical/Mechanical Engineering, Robotics, Computer Engineering, or related field; demonstrated wet-lab automation.
- Experience with lab automation systems and LIMS engineering.
- Experience integrating software/AI with lab automation (liquid handlers, analytical instruments, robotic workflows).
- Strong Docker + Kubernetes production orchestration.
- Scalable production Python apps (e.g., Redis, FastAPI, Flask/Streamlit, pytest).
Preferred
- LLM post-training/fine-tuning/RLHF; AI integrated with lab automation.
- Ability to build the translation layer from planning logic to instrument control.
- Research experience with ML/NLP publications (e.g., NeurIPS/ICML/ICLR/ACL).
Compensation/Benefits
- Anticipated wage: $87,000–$222,200; eligible for company bonus and comprehensive benefits (401(k), medical/dental/vision, vacation, life insurance, time off/leave, well-being programs).