Applied Super Intelligence Engineer, Physical Systems

Posted 2 Days Ago
Be an Early Applicant
Livermore, CA, USA
Hybrid
122K-186K Annually
Entry level
Information Technology • Security • Energy • Defense
The Role
Build software enabling intelligent agents and multimodal models to interact safely with physical equipment. Develop perception, decision-support, tool-calling, and agent workflows using camera, telemetry, APIs, and operational data. Improve prompts, evaluations, guardrails, logging, reliability, and failure analysis while collaborating with embedded, platform, and deployment engineers. The role requires Python proficiency, software engineering practices, real-world sensor or device data experience, and eligibility for a DOE Q-level clearance.
Summary Generated by Built In
Company Description

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.

Job Description

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.

Qualifications

  • 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 independently develop and evaluate multicomponent agent, multimodal, or tool-calling workflows for operational use.
  • Ability to scope and debug moderately complex workflow failures involving perception, tool use, system integration, and operational constraints.

Qualifications We Desire

  • Exposure to robotics workflows, ROS, or ROS 2.
  • Experience with vision-language models, vision-language-action models, or multimodal perception pipelines.
  • Familiarity with simulation, digital twins, or hardware-in-the-loop testing.
  • Familiarity with workflow orchestration, agent tracing or evaluation systems, prompt or configuration versioning, replay-based testing, or event and telemetry systems such as MQTT or NATS.

Pay Range

$121,830 - $185,544 Annually
$121,830 - $154,500 Annually for the SES.1 level
$146,340 - $185,544 Annually for the SES.3 level 

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage.  An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs. 

Additional Information

#LI-Hybrid

Position Information

This is a Career Indefinite position, open to Lab employees and external candidates.

Why Lawrence Livermore National Laboratory?

  • Included in 2026 Best Places to Work by Glassdoor!
  • Flexible Benefits Package
  • 401(k)
  • Relocation Assistance
  • Education Reimbursement Program
  • Flexible schedules (*depending on project needs)
  • Our values - visit https://www.llnl.gov/inclusion/our-values

Security Clearance

This position requires a Department of Energy (DOE) Q-level clearance.  If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing.  Q-level clearance requires U.S. citizenship. 

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.  

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. 

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.

Skills Required

  • Ability to secure and maintain a U.S. DOE Q-level security clearance; requires U.S. citizenship
  • Bachelor's degree in computer science, software engineering, robotics, or a related field, or equivalent education and related experience
  • Proficiency in Python or a comparable programming language
  • Experience developing LLM, multimodal, agent-based, or tool-calling applications through coursework, projects, research, internships, or professional work
  • Experience designing, implementing, testing, and debugging tool-using SI workflows connecting models to APIs, services, data sources, or operational systems
  • Experience with 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 version control, automated testing, and collaborative code review
  • Ability to independently develop and evaluate multicomponent agent, multimodal, or tool-calling workflows for operational use at SES.2 level
  • Ability to scope and debug moderately complex workflow failures involving perception, tool use, system integration, and operational constraints at SES.2 level
  • Exposure to robotics workflows, ROS, or ROS 2
  • Experience with vision-language models, vision-language-action models, or multimodal perception pipelines
  • Familiarity with simulation, digital twins, or hardware-in-the-loop testing
  • Familiarity with workflow orchestration, agent tracing or evaluation systems, prompt or configuration versioning, replay-based testing, or event and telemetry systems such as MQTT or NATS

Lawrence Livermore National Laboratory Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lawrence Livermore National Laboratory and has not been reviewed or approved by Lawrence Livermore National Laboratory.

  • Retirement Support — A 401(k) with dollar-for-dollar match up to 6% plus additional employer contributions and immediate vesting strengthens total rewards. Clear plan tracks (TCP1/TCP2) and service-based contributions add predictability and long-term value.
  • Healthcare Strength — Multiple medical, dental, and vision options, alongside FSAs and an Employee Assistance Program, provide comprehensive coverage. Ongoing open-enrollment updates and published plan details signal active plan management.
  • Leave & Time Off Breadth — Paid time off includes vacation, sick leave, and up to 12 holidays, with a paid parental leave program for bonding. Flexibility is reinforced by leave advances and a catastrophic leave-sharing program for serious needs.

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The Company
HQ: Livermore, CA
9,757 Employees
Year Founded: 1952

What We Do

Lawrence Livermore National Laboratory (LLNL) applies science and technology to make the world a safer place, focusing on national security missions such as nuclear deterrence, nonproliferation, energy security, defense, and intelligence.

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