Reverse Engineer and AI Workflow Developer

Johns Hopkins Applied Physics Laboratory•Laurel, MD

3d•Onsite

About The Position

Are you passionate about reverse engineering complex software, firmware, and hardware? Do you enjoy developing agentic AI workflows and building the infrastructure that turns emerging AI capabilities into practical tools for engineers and analysts? If so, we want you to join our team! We are seeking experienced reverse engineers and developers who are excited to combine deep technical analysis with emerging AI technologies. You will investigate complex systems, develop novel capabilities, and design AI-enabled workflows that help analysts understand systems faster and more effectively. 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, experimentation, and continuous learning. You will have opportunities to evaluate and explore new AI models and tools, develop reusable AI infrastructure, and help shape how AI is incorporated into challenging national security efforts!

Requirements

Possess a Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, Data Science, Artificial Intelligence, or another discipline relevant to the duties as described above
Have at least 2 years of experience in reverse engineering, software development, cyber analysis, AI-enabled software development, or a related technical field
Have experience reverse engineering software or firmware using tools such as Ghidra, IDA Pro, Binary Ninja, debuggers, disassemblers, or similar
Understand operating system fundamentals, computer architecture, software internals, and low-level system behavior
Have software development experience in languages such as Python, C/C++, Rust, or similar languages
Have hands-on experience using LLMs or generative AI technologies to solve software engineering, analysis, automation, or research problems
Understand the fundamentals of modern LLM-based systems, including prompting, context management, tool use, structured outputs, retrieval, and agentic workflows
Are an outstanding communicator in both written and verbal forms
Are able to acquire a Secret level security clearance by your start date and can ultimately acquire 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

Nice To Haves

Have a Master's or Ph.D. in Computer Science, Electrical Engineering, Computer Engineering, Artificial Intelligence, Machine Learning, or a related field
Have 8+ years of experience in reverse engineering, cyber capability development, software engineering, or related technical work
Have experience with AI agent frameworks, coding agents, model context protocol (MCP), retrieval-augmented generation (RAG), vector databases, or related AI infrastructure
Have experience integrating LLMs with engineering tools, reverse-engineering platforms, debuggers, compilers, source-code repositories, or other program-analysis capabilities
Have experience reverse engineering embedded systems, communications devices, radios, cellular systems, or other complex hardware/software platforms
Hold an active TS/SCI security clearance

Responsibilities

Reverse engineer software, firmware, and hardware to understand system architecture, functionality, interfaces, and behavior
Develop and apply agentic AI workflows that augment and accelerate reverse-engineering and cyber analysis tasks, combining traditional reverse-engineering techniques with AI-assisted analysis, code generation, data extraction, tool execution, and technical reasoning
Design AI agents to interface with tools, development environments, documentation and specifications, and other data sources to accomplish complex analyses
Build, configure, and maintain AI development infrastructure, including model interfaces, agent frameworks, tool integrations, model context protocol (MCP) services, retrieval systems, and supporting automation
Evaluate AI models, agent architectures, prompting strategies, tools, and workflows to understand their capabilities, limitations, reliability, and applicability to mission problems
Operationalize proof-of-concept capabilities by thoroughly testing, documenting, packaging, and integrating them into sponsor and laboratory environments