Position SummaryWe are rebuilding the Design-Make-Test-Analyze (DMTA) cycle by integrating agentic AI, cloud-based orchestration, and LIMS infrastructure to connect experimental readouts with the 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 will design agent workflows that reason over experimental data, trigger automated actions, and surface insights to scientists.
This is an on-site hands-on individual contributor role: you will prototype rapidly, productionize what works, and collaborate with chemists, biologists, and automation engineers to deploy intelligent systems that accelerate molecule discovery.
This position reports to the Agentic Automation Lead. You will own significant components of the agentic automation platform and be trusted to make technical decisions within them.
Key ResponsibilitiesIntegration Engineering- Build and maintain the translation layer between high-level agent planning logic and low-level instrument control across lab automation platforms (Hamilton, Tecan, Opentrons) and analytical instruments (LC/MS, NMR, HPLC)
- Connect experimental readouts to ELN/LIMS and downstream data pipelines so every run produces model-ready, traceable data
Agent Development- 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
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 GitOps and CI/CD practices
- Integrate cloud-based orchestration frameworks such as Argo on Kubernetes with laboratory control systems
Collaboration & External Engagement- Work directly with NVIDIA engineers and researchers and with Lilly scientists in the co-innovation lab
- Evaluate open-source projects, vendor tooling, and academic work for practical fit
What Success Looks Like- Autonomous agents reliably execute multi-step experiments on physical laboratory instruments
- Measurable reduction in DMTA turnaround through autonomous planning and execution
Basic Qualifications- PhD (or MS + 3 yrs / BS + 5 yrs equivalent experience) in Chemical / Mechanical Engineering, Robotics, Computer Science, Computer Engineering, Chemistry, or a related discipline, with demonstrated wet-lab automation experience
- Direct experience integrating software control and/or AI systems with lab automation platforms (liquid handlers, analytical instruments, robotic workflows)
Preferred Qualifications- Strong experience with containerization (Docker) and Kubernetes-based orchestration in production environments
- Experience building scalable, production-grade Python applications using tools such as Redis, FastAPI, Flask/Streamlit, and pytest (GitHub portfolio a plus)
- Hands-on experience building LLM agent or multi-agent systems that call real tools in production
- Experience with LLM post-training, fine-tuning, or RLHF
- Experience with self-driving labs, autonomous experimentation, or high-throughput experimentation (HTE) workflows
- Proven ability to build and maintain the translation layer between high-level planning logic and low-level instrument control
- Familiarity with the NVIDIA stack for life sciences (BioNeMo, CUDA, Omniverse)
- Experience mentoring interns, students, or junior engineers (this is a growth path, not a requirement)
- 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) or leading chemistry journals
This is an onsite position based in South San Francisco, CA.
Actual compensation will depend on a candidate's education, experience, skills, and geographic location. The anticipated wage for this position is
$168,000 - $268,400
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly's compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
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