AI Assurance Engineer for Mission-Critical Defense

Johns Hopkins Applied Physics Laboratory; Laurel (MD); On-site; USD 100,000 - 245,000; Full time

Job summary

Johns Hopkins Applied Physics Laboratory in Laurel, MD seeks an AI Assurance Engineer to design and execute comprehensive evaluations of generative AI models and agentic systems used in defense and healthcare. You will develop test plans, benchmarks, and risk-based criteria to ensure safety, reliability, and mission readiness.

The role requires collaboration with researchers and engineers, presenting results to sponsors, and supporting deployment decisions in high-stakes environments.

Qualifications

• Bachelor's degree in CS, Data Science, AI, ML, Statistics, Cybersecurity, or related field.
• Experience with Python and software development for AI, data analysis, or test automation.
• Familiarity with generative AI models, agentic systems, or ML concepts and the AI threat landscape.
• Knowledge of test and evaluation principles, including developing test cases, defining success criteria, and analyzing results.
• Strong analytical, written, and verbal communication skills, with the ability to collaborate in a multidisciplinary team.
• Ability to obtain an Interim Secret level security clearance by start date and ultimately Top-Secret; US citizenship required.

Responsibilities

• Design and execute assurance evaluations for generative AI models and agentic systems for 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.

Skills

Python

AI model evaluation

Test automation

Data analysis

Communication

Education

Bachelor's degree in a technical field

Master's degree or higher in a related field

Job description

Johns Hopkins Applied Physics Laboratory in Laurel, MD seeks an AI Assurance Engineer to design and execute comprehensive evaluations of generative AI models and agentic systems used in defense and healthcare. You will develop test plans, benchmarks, and risk-based criteria to ensure safety, reliability, and mission readiness.

The role requires collaboration with researchers and engineers, presenting results to sponsors, and supporting deployment decisions in high-stakes environments.