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Applied Super Intelligence Engineer

  • Hybrid

Salary

$120,000 - 190,000/ year

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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.

Responsibilities

  • 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.

Requirements

  • 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.
  • 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.

Conditions

$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 the company's site

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 (the company) to post fake job advertisements. The company 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: the company's site

Where you’d work

Part of the week in the office

You can work from

  • United States

Relocation offered

No visa sponsorship

About the company

Company hidden

Office in CA, United States

Your chances

Still hiring, not crowded yet, and you'd be among the first.

  • 18 checks run
  • 4 good signs
  • 1 red flag

Still hiring?

11 checks

Actively hiring

In its favour3

  • Still on the company's own careers site, checked 1 h agoModerate evidence
  • Found in the last 48 hours, before the big job boardsModerate evidence
  • States its salarySlight evidence

How crowded?

7 checks

Low

In its favour1

  • In its Early Window: not on the big job boards yetStrong evidence

Against it1

  • Offers relocation: people from other countries apply tooSlight evidence

Fits Me

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Details11 facts · Role, Location, Compensation, Employment
Tech stack
  • Python
  • LLMs
Type
Full-time
Region
United States
Pay period
Annual
Show 7 more factsShow less

Role

Category
Development
Tech stack
  • Python
  • LLMs

Location

Work model
Hybrid
Region
United States
Office
  • CA, United States
Remote from
  • United States
Relocation
Offered
Visa sponsorship
Not sponsored

Compensation

Salary
$120,000 - 190,000 / year
Pay period
Annual

Employment

Type
Full-time

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