Advisor - Lab Automation Software Engineer, AI-Integration

Job Summary

The Biologics Automation and High-throughput Technologies Group at the Lilly Biotechnology Center in San Diego is seeking an Advisor Lab Automation Software Engineer to lead the design and implementation of reliable software integrations between orchestration layers and physical lab systems.

About the Role

Our team is working toward a vision of closed-loop autonomous discovery — where robotic platforms, lab digitalization, and AI-driven orchestration work together to accelerate how biologics are found and developed. In this role, you will own the software integration layer between our automation infrastructure and the digital tools that drive it, while helping to shape how emerging AI capabilities get woven into that foundation over time.

Responsibilities

• Lab Automation Integration
  • Lead the design and implementation of reliable software integrations between orchestration layers and physical lab systems including liquid handlers, plate readers, robotic workstations, and analytical instruments.
  • Own and evolve the translation layer between high-level workflow logic and low-level instrument control.
  • Partner with automation engineers and biologists to ensure integrations are robust, maintainable, and production-ready.
• Platform & Infrastructure
  • Deploy and maintain containerized services using Docker and Kubernetes with GitOps and CI/CD practices.
  • Integrate cloud-based orchestration frameworks with laboratory control systems and LIMS infrastructure.
  • Build scalable, production-grade Python applications and data pipelines that connect experimental readouts with downstream analysis tools.
• AI & Intelligent Automation
  • Collaborate with the team to explore and prototype how AI-driven decision-making can be incorporated into existing automation workflows.
  • Contribute to the team's evolving approach to autonomous orchestration, bringing software engineering rigor to early-stage AI integration efforts.
• Technical Leadership
  • Serve as a technical authority and mentor within the automation engineering team, helping to grow capability across software, integration, and emerging AI systems.
  • Influence the broader technical roadmap for autonomous discovery systems at the San Diego site.
  • Evaluate tools, frameworks, and vendor solutions for strategic fit with the team's long-term vision.

Qualifications

• Ph.D. in Computer Science, Software Engineering, Bioengineering, or related discipline with a minimum of 3 years of relevant industry experience, or M.S. in a related discipline with a minimum of 5 years of relevant industry experience, or B.S. in a related discipline with a minimum of 8 years of relevant industry experience.
• Demonstrated experience integrating software systems with laboratory automation platforms is required across all levels.

Preferred Skills & Attributes

• Strong Python development skills with proven experience building and maintaining production-level applications (FastAPI, Redis, Flask, pytest, etc.).
• Deep hands-on experience with Docker, Kubernetes, and CI/CD pipelines in production environments.
• Experience with cloud-based orchestration frameworks such as Argo on Kubernetes.
• Direct experience integrating software control systems with lab automation platforms (liquid handlers, analytical instruments, robotic workflows).
• Familiarity with scheduling and execution software used in integrated lab environments (Cellario, Green Button Go, Director, SAMI, VWorks, Genera, or similar).
• Experience with LIMS platforms, ELN systems, or laboratory data pipelines.
• Curious about and some hands-on experience with LLMs, agent frameworks, or AI-driven workflow automation.
• Familiarity with orchestration tools such as LangChain, LangGraph, or similar.
• Proven ability to move fluidly between architectural thinking and hands-on engineering execution.
• Strong collaboration skills — comfortable working across software, automation engineering, and biological science teams.
• Genuine curiosity about biologics discovery and a desire to understand the science well enough to build systems that truly serve it.