Advisor - Lab Automation Software Engineer, AI-Integration

In this role, you will have the opportunity to

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
• Stay current with developments in LLM tooling and agent frameworks and help evaluate what is practically applicable to the lab environment

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

What Success Looks Like

• Lab automation systems are reliably connected, well-instrumented, and generating clean data that flows seamlessly into digital workflows
• The team's software architecture evolves from early-stage integrations toward scalable, production-grade infrastructure
• AI capabilities are thoughtfully and pragmatically incorporated into automation workflows as the field matures
• Your technical leadership accelerates the capability growth of the broader automation engineering team

Basic 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

Software Engineering & Infrastructure

• 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

Lab Automation & Integration

• Direct experience integrating software control systems with lab automation platforms (liquid handlers, analytical instruments, robotic workflows)
• Hands-on familiarity with common biologics discovery instrumentation - liquid handlers (Beckman, Hamilton, HighRes, etc.), micro-dispensers, plate readers, or integrated robotic workstations - is a strong plus
• 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

AI & Emerging Technologies

• Curiosity 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 is a plus - deep expertise is not expected
• Demonstrated willingness to learn and experiment with new technologies as they emerge
• General
• 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

Additional information

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women's Initiative for Leading at Lilly (WILL).

Actual compensation will depend on a candidate's education, experience, skills, and geographic location. The anticipated wage for this position is $157,500 - $231,000

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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