Sr. Principal or Engineering Advisor - Agentic Lab Automation Integration

Scorpion Therapeutics; San Diego (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Scorpion Therapeutics is seeking an engineer to bridge agentic AI with physical lab systems in San Diego. You will design workflows that reason over experimental data, trigger automated actions, and surface insights for scientists.

You'll prototype rapidly, productionize solutions, and collaborate with chemists, biologists, and automation engineers to deploy intelligent systems that accelerate molecule discovery. Expertise in Docker, Kubernetes, and Python is valued.

Qualifications

• PhD in Chemical/Mechanical Eng, Robotics, Computer Eng, or related field; wet-lab automation exp.
• Experience with laboratory automation systems and LIMS engineering.
• Experience integrating software control and AI with lab automation (liquid handlers, instruments, workflows).
• Strong Docker and Kubernetes orchestration experience in production.
• Production-grade Python apps (Redis, FastAPI, Flask/Streamlit, pytest).

Responsibilities

• Engineer the connective tissue between agentic AI and lab systems.
• Design agent workflows that reason over experimental data and surface insights.
• Prototype rapidly, productionize effective solutions.
• Collaborate with chemists, biologists, and automation engineers to deploy intelligent systems.
• Interface agent architectures with lab automation platforms for closed-loop execution.
• Deploy containerized services with CI/CD in production.

Skills

wet-lab automation

AI workflow design

Python development

systems integration

Education

PhD or MS + 2 yrs / BS + 5 yrs in relevant field

Tools

Docker

Kubernetes

Redis

FastAPI

pytest

LIMS

Job description

Position Summary

• Engineer the connective tissue between agentic AI and physical lab systems, integrating with robotic platforms, analytical instruments, and data pipelines.


• Design agent workflows that reason over experimental data, trigger automated actions, and surface insights to scientists.


• Prototype rapidly, productionize effective solutions, and collaborate with chemists, biologists, and automation engineers to deploy intelligent systems that accelerate molecule discovery.

Research & Innovation

• Build multi-agent systems with orchestration, state management, error recovery, and tool integration.


• Prototype and iterate on agent planning, memory systems, and human-in-the-loop patterns.


• Interface agent architectures with lab automation platforms (Hamilton, Tecan, Opentrons) for closed-loop execution.

Solution Deployment

• Transition prototypes into reliable lab operations with automation engineers and scientists.


• Deploy and maintain containerized services using Docker and Kubernetes with GitOps and CI/CD.


• Integrate cloud orchestration (e.g., Argo on Kubernetes) with laboratory control systems.

External Engagement

• Publish, give talks, review papers, and scout emerging trends in AI@Lilly and external communities.


• Evaluate vendors, open-source projects, and academic collaborations.

Basic Qualifications

• PhD (or MS + 2 yrs / BS + 5 yrs) in Chemical/Mechanical Engineering, Robotics, Computer Engineering, or related field; demonstrated wet-lab automation experience.


• Experience with laboratory automation systems and LIMS engineering.


• Experience integrating software control and/or AI systems with lab automation (liquid handlers, analytical instruments, robotic workflows).


• Strong containerization (Docker) and Kubernetes orchestration experience in production.


• Scalable production Python applications (e.g., Redis, FastAPI, Flask/Streamlit, pytest).

Preferred

• LLM post-training (fine-tuning, RLHF).


• Integrate AI/decision systems with lab automation.


• Build/maintain translation layer between planning logic and instrument control.


• Research contributions/publications (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR).