Autonomous Lab Automation Engineer - AI-Driven Orchestration

100 Eli Lilly and Company; San Diego (CA); On-site; USD 141,000 - 207,000; Full time

Benefits offered by this job

401(k) plan

Pension

Vacation benefits

Medical, dental, vision coverage

Flexible benefits

Life insurance

Time off and leave

Well-being benefits

Job summary

Lilly’s Biologics Automation team in San Diego seeks an Advisor Lab Automation Software Engineer to bridge automation and digital tools in antibody discovery. You will own the software integration layer, deploy containerized services, and help weave AI into automation workflows.

You will lead design, implement robust lab-system integrations, and mentor the automation engineering team while exploring AI-driven decision-making and scalable data pipelines.

Qualifications

• PhD/MS/BS with strong software and lab automation integration experience.
• Experience integrating software with laboratory automation platforms.
• Production-grade Python and data pipelines experience.

Responsibilities

• Lead software integrations between orchestration layers and lab systems.
• Develop containerized services with Docker/Kubernetes and CI/CD.
• Prototype AI-driven automation and ensure robust, scalable solutions.
• Collaborate across software, automation engineering, and biology teams.

Skills

Python development

Docker

Kubernetes

CI/CD pipelines

AI integration

LangChain familiarity

Cloud orchestration

Team mentorship

Education

PhD in CS/Software Eng/Bioengineering

MS in related discipline

BS in related discipline

Tools

FastAPI

Redis

Flask

pytest

Argo on Kubernetes

GitOps

Job description

Lilly’s Biologics Automation team in San Diego seeks an Advisor Lab Automation Software Engineer to bridge automation and digital tools in antibody discovery. You will own the software integration layer, deploy containerized services, and help weave AI into automation workflows.

You will lead design, implement robust lab-system integrations, and mentor the automation engineering team while exploring AI-driven decision-making and scalable data pipelines.