AI-Enabled Cyber Capabilities Developer
$105kJohns Hopkins Applied Physics Lab
Description Are you passionate about building AI-enabled capabilities that accelerate reverse engineering and vulnerability research? Do you want to design systems that can reason, plan, use tools, and rapidly demonstrate mission impact? If so, we want you to join our group of offensive cyber experts! We are seeking reverse engineers, vulnerability researchers, and cyber capability developers who know how to leverage modern AI technology to solve complex cyber challenges. This is not a traditional software development role! It requires designing AI-native architectures, orchestrating tool-using agents, and rapidly iterating on prototypes that demonstrate functional, outcome-driven impact. We work in a dynamic, mission‑driven environment where our efforts have real‑world impact. Collaboration is at the heart of our culture, and we value multidisciplinary perspectives, curiosity, and continuous learning. We encourage our staff to explore emerging technologies, share knowledge, and deepen their expertise as they take on some of the nation’s toughest challenges. As a member of our group, you will… Reverse engineer mission-relevant systems and develop innovative exploits Design and implement agentic AI systems to automate vulnerability research, reverse engineering, and capability development workflows Collaborate with government sponsors and operators to build mission-aligned capabilities Integrate large language models, AI services, external tools, and data sources into full-stack applications for cyber use cases Propose groundbreaking ideas for internal and external funding opportunities Mentor teammates in the art and science of using AI to enhance offensive cyber capability development Share knowledge by clearly articulating ideas through papers and presentations to team members, APL management, and government decision makers Qualifications Minimum qualifications for the job are: Have a Bachelor’s degree in Computer Engineering, Computer Science, Electrical Engineering, or a related field At least 5 years of relevant experience Have experience developing agentic AI systems including planning, memory, tool use, and multi-step reasoning workflows Are skilled with software debuggers and static analysis tools such as Ghidra Have experience with modern AI development platforms such as Claude Code, Gemini, Codex, or Copilot Are proficient with one or more programming languages Understand Unix/Linux operating systems Love solving puzzles and have experience persevering through technical challenges Hold an active TS/SCI clearance and can ultimately obtain a TS/SCI+Polygraph 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 will go above and beyond our minimum requirements if you: Previously held dynamic technical leadership roles and have demonstrated mentoring experience Have experience applying AI systems to reverse engineering, vulnerability research, or exploit development Have experience designing production-grade agent workflows, including orchestration, evaluation, guardrails, observability, and reliability testing Have familiarity with virtualization, emulation, sandboxing, or automated analysis environments Have knowledge of advanced vulnerability discovery tools Possess an active TS/SCI clearance with full scope polygraph About Us The Johns Hopkins University Applied Physics Laboratory (APL) brings world‑class expertise to our nation’s most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates. At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL’s campus is located in the Baltimore‑Washington metro area. Learn more about our career opportunities at 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. The referenced pay range is based on JHU APL’s good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign‑on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short‑term disability, long‑term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis. Minimum Rate $105,000 Annually Maximum Rate $290,000 Annually #J-18808-Ljbffr Johns Hopkins Applied Physics Lab
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