Sr. Principal or Engineering Advisor - Agentic Lab Automation Integration

Eli Lilly Eli Lilly · Pharma · Indianapolis, IN +6

This role focuses on engineering the integration between agentic AI and physical lab systems, specifically for automating and accelerating molecule discovery in a healthcare setting. The engineer will build multi-agent systems, design agent workflows that interact with lab automation platforms, and deploy these systems into production environments. The goal is to create autonomous agents that can execute experiments, reduce experimental cycle times, and become integral to lab operations.

What you'd actually do

  1. Build multi-agent systems with robust orchestration, state management, error recovery, and tool integration
  2. Prototype and iterate rapidly on agent planning strategies, memory systems, and human-in-the-loop patterns
  3. Design agent architectures that interface with lab automation platforms (Hamilton, Tecan, Opentrons) for closed-loop experimental execution
  4. Partner with automation engineers and scientists to transition prototypes into reliable lab operations
  5. Deploy and maintain containerized services using Docker and Kubernetes with GitOps and CI/CD practices

Skills

Required

  • 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.

Nice to have

  • 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 (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR)

What the JD emphasized

  • laboratory automation systems
  • LIMS engineering
  • liquid handlers
  • analytical instruments
  • robotic workflows
  • Docker
  • Kubernetes

Other signals

  • integrating agentic AI
  • lab automation
  • autonomous design, run, and refine experiments
  • multi-agent systems
  • orchestration
  • tool integration
  • experimental data
  • robotic platforms
  • analytical instruments
  • data pipelines