AI Innovation Engineer

Basic Qualifications

Bachelor's degree in Systems Engineering, or a related Science, Engineering or Mathematics field, plus a minimum of 5 years of relevant experience; or Master's degree, plus a minimum of 3 years of relevant experience.

CLEARANCE REQUIREMENTS: Department of Defense Secret security clearance is obtainable within a reasonable amount of time after hire. Applicants selected will be subject to a U.S. Government security investigation and must meet eligibility requirements for access to classified information. Due to the nature of work performed within our facilities, U.S. citizenship is required. Candidate must be able to work onsite.

Responsibilities for this Position

As an AI Innovator supporting Strategic Mission Systems Programs , you’ll be a member of a cross-functional team turning emerging AI capabilities into practical solutions for some of our programs’ most challenging engineering and execution challenges. You’ll explore new technology, build and test AI-enabled tools, and reimagine workflows that help our teams work smarter, improve quality, and deliver mission-critical capabilities for our nation’s security.

We encourage you to apply if you have any of these preferred skills or experiences:

• Hands-on AI experimentation and solution development: Experience using generative AI, scripting, software development, or automation to create useful tools or significantly improve existing workflows. • Engineering and program problem-solving: Experience applying systems engineering, requirements management, system modeling, or process improvement to solve complex technical or program challenges. • Turning ideas into measurable results: Experience prototyping solutions, evaluating performance, incorporating user feedback, and demonstrating improvements in efficiency, quality, or usability.

What you’ll do:

• Turn difficult program challenges into opportunities for innovation. Partner with engineers, program teams, and AI Champions to identify repetitive tasks, workflow bottlenecks, and complex problems where AI can make a meaningful difference. • Build, experiment, and improve. Design, develop, and refine AI-enabled tools, workflows, and processes, moving from a focused concept to a practical solution that meets real user needs. • Explore emerging capabilities. Test and evaluate new AI models, features, tools, and supporting frameworks when needed, with an emphasis on technical capability, integration, and solution development. • Make reliability and responsible use part of the design. Evaluate solutions for usefulness, accuracy, reliability, security, and suitability for their intended application; provide timely, constructive feedback on benefits, limitations, defects, and risks. • Demonstrate impact. Establish practical measures of success and show how your innovations save time, improve quality, reduce effort, or make information and workflows more accessible. • Help successful ideas reach more teams. Document solution functionality, limitations, and responsible-use considerations; partner with AI Champions to share demonstrations, incorporate feedback, and support broader adoption. • Reuse what works. Explore existing approved tools, assistants, automation patterns, and enterprise services before building something new, and share reusable approaches that other programs can adapt.