Applied Super Intelligence Engineer, Physical Systems

Applied Super Intelligence Engineer, Physical Systems

• Full-time
• Job Code 2: SES.
  2 Science & Engineering MTS 2
• Employee Referral Bonus: $1500
• Job Code 1: SES.
  1 Science & Engineering MTS 1
• Pre-Employment Drug Test:
  Required for external applicant(s) selected for this position (includes testing for use of marijuana)
• Pre-Placement Medical Exam:
  Not applicable
• Security Clearance:
  Anticipated DOE Q clearance (requires U.S. citizenship and a federal background investigation)

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

We are seeking an Applied Super Intelligence (SI) Engineer, Physical Systems, to help build software that enables SI agents and multimodal models to interact with real-world equipment through an existing hardware integration stack. You will focus on applied SI and perception workflows that transform operational data and equipment interfaces into safe, usable SI-assisted systems. This position is in the Material Engineering Division (MED) within the Engineering Directorate.

This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home one or more days per week.

This position will be filled at either level based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities (outlined below) will be assigned if hired at the higher level.

You will

• Implement agent-facing tool definitions and task workflows that use documented equipment interfaces and platform services.
• Develop multimodal perception and decision-support workflows using camera, telemetry, and process data.
• Improve prompt logic, tool use, evaluation methods, and workflow reliability for physical-world SI applications.
• Translate real-world operational tasks into practical SI-assisted workflows that are usable, testable, and maintainable.
• Work with embedded, platform, and deployment engineers in a controlled environment to define safe action boundaries, human- or system-mediated approval points, and fallback behaviors using established external safety and security systems.
• Evaluate and debug applied SI workflows through comprehensive logging, iterative refinement, and disciplined engineering practices.
• Perform other duties as assigned.

Additional job responsibilities, at the SES.
2 level

• Design and evaluate agent workflows that combine perception, tool use, and equipment actions across multiple system components, input modalities, and operational steps.
• Improve reusable evaluation harnesses, guardrails, and failure analysis for SI-assisted workflows, using the results to guide technical decisions.
• Coordinate with embedded and SI platform engineers to translate device capabilities, operational requirements, and workflow evaluation results into reusable agent workflows, while providing informal guidance to less-experienced contributors.
• Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
• Bachelor’s degree in computer science, software engineering, robotics, or a related field, or an equivalent combination of education and related experience.
• Proficiency in Python or a comparable programming language for building applications, prototypes, or internal tools in collaboration with software and systems engineers.
• Experience gained through coursework, projects, research, internships, or professional work developing LLM, multimodal, agent-based, or tool-calling applications.
• Experience designing, implementing, testing, and debugging tool-using SI workflows that connect models to APIs, services, data sources, or operational systems, including structured tool or API contracts, such as JSON Schema or OpenAPI, error handling, logging, and evaluation.
• Experience working with real-world data from sensors, cameras, devices, or operational systems.
• Familiarity with sound software development practices, including version control, automated testing, and collaborative code review.

Additional qualifications at the SES.
2 level

• Ability to…