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Sr. Principal or Engineering Advisor - Agentic Lab Automation Integration

Job in South San Francisco, San Mateo County, California, 94083, USA
Listing for: Eli Lilly and
Full Time position
Listed on 2026-02-28
Job specializations:
  • Engineering
    AI Engineer, Systems Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Organization Overview

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life‑changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first.

We’re looking for people who are determined to make life better for people around the world.

Frontier AI

Frontier AI is a purpose‑built team that fuses scientific agentic AI, lab automation, and unified data platforms to autonomously design, run, and refine experiments—accelerating molecule discovery.

Position Summary

We are rebuilding the Design‑Make‑Test‑Analyze (DMTA) cycle by integrating agentic AI, cloud‑based orchestration, and LIMS infrastructure to connect experimental readouts with tools that accelerate laboratory science.

You will engineer the connective tissue between Agentic AI and physical lab systems building practical integrations with robotic platforms, analytical instruments, and data pipelines. You'll design agent workflows that reason over experimental data, trigger automated actions, and surface insights to scientists. This is a hands‑on engineering role: you'll prototype rapidly, product ionize what works, and collaborate with chemists, biologists, and automation engineers to deploy intelligent systems that accelerate molecule discovery tasks.

Research

& Innovation
  • Build multi‑agent systems with robust orchestration, state management, error recovery, and tool integration.

  • Prototype and iterate rapidly on agent planning strategies, memory systems, and human‑in‑the‑loop patterns.

  • Design agent architectures that interface with lab automation platforms (Hamilton, Tecan, Opentrons) for closed‑loop experimental execution.

Solution Deployment
  • Partner with automation engineers and scientists to transition prototypes into reliable lab operations.

  • Deploy and maintain containerized services using Docker and Kubernetes with Git Ops and CI/CD practices.

  • Integrate cloud‑based orchestration frameworks such as Argo on Kubernetes with laboratory control systems.

External Engagement
  • Represent Frontier AI in the broader AI@Lilly and external AI research community: publish, give talks, review papers, and scout emerging trends.

  • Evaluate external vendors, open‑source projects, and academic collaborations for strategic fit.

What Success Looks Like
  • Autonomous agents reliably execute experiments on physical laboratory instruments.

  • Measurable reduction in DMTA turnaround through autonomous planning and execution.

  • Agents you build become indispensable to the automation engineering community.

  • Frontier AI platforms scale from pilot deployments to production lab environments.

Basic Qualifications
  • PhD (or MS + 2 yrs / BS + 5 yrs equivalent experience) in Chemical / Mechanical Engineering, Robotics, Computer Engineering, or related discipline with demonstrated wet‑lab automation experience.

  • Demonstrated experience with laboratory automation systems and LIMS engineering.

  • Direct experience integrating software control and/or AI systems with lab automation platforms (liquid handlers, analytical instruments, robotic workflows).

  • Strong experience with containerization (Docker) and Kubernetes‑based orchestration in production environments.

  • Experience building scalable and production‑level python applications using tools like Redis, FastAPI, flask/streamlit, pytest, etc. (Git Hub portfolio a plus).

Preferred
  • Experience with LLM post‑training, fine‑tuning, or RLHF.

  • Direct experience integrating AI or algorithmic decision systems with laboratory automation.

  • Proven ability to build and maintain the translation layer between high‑level planning logic and low‑level instrument control.

  • Demonstrable research experience, evidenced by contributions to projects, and ideally through publications in relevant ML/NLP venues (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR).

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal…

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