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Nvidia Artificial Intelligence Engineer Jobs (NOW HIRING)

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As of Sep 10, 2026, the average yearly pay for nvidia artificial intelligence engineer in the United States is $106,386.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,000.00 and $132,500.00 per year, depending on experience, location, and employer.

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Infographic showing various Nvidia Artificial Intelligence Engineer job openings in the United States as of June 2026, with employment types broken down into 76% Full Time, 16% Part Time, and 8% Contract. Highlights an 87% Physical, 6% Hybrid, and 7% Remote job distribution, with an average salary of $106,386 per year, or $51.1 per hour.

Artificial Intelligence Engineer

Washington, DC โ€ข On-site

Triumph Enterprises, Inc
Business Management Consultingย โ€ขย 51 - 200 employees

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Posted 5 days ago


Job description

Join our team of high performers seeking to change the status quo.

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Triumph Enterprises is building the team for a Department of Veterans Affairs Office of Information and Technology / Office of Information Security (OIT/OIS) program covering enterprise cybersecurity architecture and engineering. We are seeking an Artificial Intelligence Engineer to apply machine learning and large language models to cybersecurity operations and to own the evaluation methodology that determines whether an AI capability is fit to deploy.

Program: VA Cybersecurity Architecture and Engineering Services (COSE)
Location: Washington, DC (Remote) | Full-Time, Exempt | Contingent upon contract award

This is a build-and-prove role in equal measure. Our technical approach commits to a six-pillar validation framework applied before any AI capability is deployed, with testing mapped to each pillar. The engineer in this seat is accountable both for the automation that gets built and for the defensible evidence that it should be trusted in a Federal security environment.

RESPONSIBILITIES
  • - Design, build, and operate AI and machine learning capabilities supporting cyber tool integration and security operations automation.
  • - Own the six-pillar AI validation framework: categorize, test, and validate AI technologies before deployment, with testing traceable to each pillar.
  • - Deliver the Autonomous Workflow Library, jointly with the DevSecOps Engineer.
  • - Produce the quarterly Security Control Effectiveness Report.
  • - Maintain the AI System / LLM Development and Operation Documentation Package.
  • - Issue AI Model / LLM Change Disclosures no later than 30 days prior to any model change.
  • - Meet the AI attestation and disclosure obligations the program carries, and document model behavior and changes for a Government audience.
  • - Partner with the Cloud Security Architect and DevSecOps Engineer to integrate AI capability into the enterprise security toolset without expanding the attack surface.
REQUIRED QUALIFICATIONS
  • - Minimum 10 years of information technology experience, with demonstrated applied machine learning or LLM engineering in a security or operations context.
  • - Master's degree in Cybersecurity, Computer Science, Information Systems, Information Assurance, Information Security, Data Science, or a related field.
  • - A defensible, documented methodology for categorizing, testing, and validating AI technologies prior to deployment.
  • - Working knowledge of Federal AI governance obligations, including attestation and disclosure requirements.
  • - Ability to write model behavior and change documentation that will stand up to Government review.
  • - Proficiency in Python and modern ML/LLM tooling, and the engineering discipline to move a model from prototype to a supportable production capability.
CERTIFICATION (REQUIRED)

One or more of the following: Information Assurance Technician (IAT) III, Information Assurance Management (IAM) III, or Information Assurance System Architect and Engineer (IASAE) III. Commonly satisfied by CISSP, CISSP-ISSEP, CISM, or CASP+. Certification is verified against the current DoD 8140 qualification matrix before an offer is extended. The credentials named above are those most commonly held; any other credential on the current matrix at the required level also qualifies.

Note to applicants: this combination -- senior AI/ML engineering plus a DoD 8570 Level III certification -- is uncommon. If you hold the technical depth and are actively pursuing the certification, we want to talk to you.

This position requires a Tier 4 / High Risk Public Trust background investigation. A Tier 4 investigation is adjudicated for suitability and fitness and is not a security clearance. Candidates must be U.S. citizens and able to obtain and maintain the investigation, VA systems access, and PIV credentialing. No work may begin until an interim determination is received.

PREFERRED
  • - NIST AI Risk Management Framework experience.
  • - Security operations automation using large language models -- triage, enrichment, detection engineering, or response orchestration.
  • - Published or otherwise demonstrable AI evaluation methodology.
  • - Experience deploying models in a FedRAMP or Federal cloud environment.
  • - Prior VA program experience, particularly within OIT or OIS.
ADDITIONAL INFORMATION

Travel is expected to be 0-10%. This position is contingent upon contract award.

Triumph Enterprises, Inc. is an SBA-certified Service-Disabled Veteran-Owned Small Business and an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by law.

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