Artificial Intelligence National Security Analyst

Description Are you searching for important work at the intersection of National Security Analysis and Generative AI? Are you interested in contributing to the evolution of analytic tradecraft by integrating emerging AI capabilities into real-world operational problems? If so, we’re looking for someone like you to join our team at APL, helping shape how AI enhances National Security Analysis. In this role, you will build, explore, evaluate, and apply Generative AI tools—including large language models—to augment analytic workflows, improve insight generation, and enhance decision support. Working within the Advanced Mission Modeling and AI Group (JAM) in the National Security Analysis Department (NSAD), you will play a key role in integrating AI into analytic methodologies used across DoD and Combatant Command efforts, providing critical solutions to critical challenges. Responsibilities Develop and apply Generative AI tools to support and enhance National Security Analysis workflows. Evaluate AI capabilities for reliability, usefulness, and limitations within real-world mission contexts. Integrate AI-assisted approaches into existing analytic techniques to improve speed, scale, and insight generation. Develop and refine prompting strategies and workflows to support analytic tasks. Collaborate with analysts, engineers, and developers to translate mission needs into AI-enabled solutions. Help define, document, and communicate best practices for applying AI across the National Security Analysis space. Qualifications You meet our minimum qualifications for the job if you: Possess a Bachelor’s degree in a relevant field such as Computer Science, Data Science, Engineering, or a closely related discipline. Have at least three years of relevant experience in National Security Analysis, operations analysis, or related analytic work. Have familiarity with Generative AI tools (e.g., large language models) and their application to real-world problems. Have experience applying structured analytic methods to complex problem sets. Possess strong critical thinking skills and the ability to evaluate the reliability and limitations of analytic outputs. Have basic technical fluency, including light scripting or experience working with data and tools (e.g., Python, APIs, or similar). Are able to communicate analytic insights clearly in both written and verbal formats. Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a TS/SCI level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship. You go above and beyond our minimum requirements if you: Have experience applying/integrating Generative AI approaches in analytic, research, or operational contexts. Have familiarity with prompt engineering, retrieval-augmented generation (RAG), or AI-assisted workflows. Have experience evaluating AI outputs for bias, accuracy, and mission relevance. Have experience supporting DoD or IC analytic efforts. Have worked with integrating new tools or technologies into established analytic processes. Have experience briefing analytic insights to stakeholders. Compensation Minimum Rate: $100,000 Annually Maximum Rate: $245,000 Annually EEO Statement All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact View email address on click.appcast.io. #J-18808-Ljbffr Johns Hopkins Applied Physics Laboratory