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Johns Hopkins Applied Physics Laboratory

Not-for-profit UARC delivering national security research

AI Assurance Engineer

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeLaurel, MD, USAIn-person

About the Job

Requirements

  • A Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Cybersecurity, or another relevant technical field.
  • Experience with Python and software development for AI, data analysis, or test automation.
  • Familiarity with generative AI models, agentic systems, or machine learning concepts and the AI threat landscape.
  • Knowledge of test and evaluation principles, including developing test cases, defining success criteria, and analyzing results.
  • Ability to obtain an Interim Secret level security clearance by the start date and ultimately obtain a Top-Secret level clearance; eligibility requirements include U.S. citizenship.

Responsibilities

  • Design and execute assurance evaluations for generative AI models and agentic systems supporting defense and healthcare missions.
  • Develop test strategies, evaluation plans, test cases, and success criteria to assess AI performance, security, robustness, and mission suitability.
  • Apply AI evaluation methods, benchmarks, and test frameworks to identify model limitations, vulnerabilities, and assurance risks.
  • Collaborate with AI researchers, engineers, and mission partners to advance AI assurance capabilities and support operational deployment.
  • Analyze evaluation results and communicate technical findings, recommendations, and assurance decisions to government sponsors.
  • Evaluate AI capabilities in realistic mission environments to enable informed, risk-based deployment decisions.

Desired Qualifications

  • A Master's degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, Cybersecurity, or a related technical field.
  • Familiarity with AI risk management frameworks, assurance best practices, and governance principles for deploying trustworthy AI systems.
  • Experience evaluating generative AI models or agentic systems using AI benchmarks, test frameworks, or adversarial testing methodologies.
  • Experience presenting technical findings, risk assessments, and evaluation results to senior leaders, government sponsors, or other technical and non-technical stakeholders.

About the Company

Johns Hopkins Applied Physics Laboratory

Not-for-profit UARC delivering national security research

Johns Hopkins Applied Physics Laboratory (APL) is a not-for-profit university-affiliated research center that provides solutions to complex national security and scientific challenges through technical expertise, prototyping, research and development, and analysis. It uses engineering, simulations, and studies to design prototypes and deliver analyses that support government and partner organizations. Unlike many commercial firms, APL operates as a non-profit affiliated with Johns Hopkins and focuses on mission-oriented research rather than selling finished products. Its goal is to provide practical, thoroughly tested solutions to public-sector customers by performing research, developing prototypes, and offering expert analysis.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
United States
Founded
1942

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