Sr Systems Engineer (AI/ML Integration)
- Compensation
- $105K–$157K
- Location
- Lexington Park, Maryland
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Contract
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- Education: Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, Systems Engineering, or related STEM field.
- Experience: Minimum eight (8) years of experience supporting the design, integration, test, acquisition, or sustainment of complex aerospace, aviation, autonomous, or defense systems. Minimum three (3
- Security Clearance: Active Secret security clearance with ability to obtain and maintain a Top Secret clearance. U.S. Citizenship required.
Nice to have
- Master's degree in Systems Engineering, Electrical Engineering, Computer Engineering, Computer Science, or a related technical discipline.
- Experience supporting AI/ML-enabled systems, autonomous systems, sensor fusion, decision-support systems, or advanced analytics capabilities.
- Understanding of machine learning concepts, model development lifecycles, data management practices, and AI system integration considerations.
- Experience evaluating AI/ML architectures and technical approaches for operational defense applications.
- Previous experience supporting NAVAIR programs or military aviation systems.
- Experience supporting unmanned aviation platforms, particularly MQ-9 or similar Group 4/5 UAS programs. INCOSE ASEP, CSEP, or ESEP certification, or DAWIA certification.
- Experience preparing engineering reports, technical correspondence, and executive-level briefing materials using Microsoft Office applications.
Full description
Title:
Sr Systems Engineer (AI/ML Integration)
Program Summary: This position supports tasking at the Naval Air Systems Command (NAVAIR) Program Executive Office for Unmanned Aviation and Strike Weapons (PEO(U&W)) located in Patuxent River, Maryland. The selected candidate will support the Smart Sensor team in the development, integration, testing, acquisition, and sustainment of advanced unmanned aviation capabilities. This role focuses on the application of Artificial Intelligence (AI) and Machine Learning (ML) technologies to support mission effectiveness, operational decision-making, and autonomous system capabilities across the MQ-9 program portfolio.
Job Summary: KBR is seeking a Senior Systems Engineer (AI/ML Integration) to provide technical leadership supporting AI/ML-enabled capabilities within the MQ-9 Program Office. The selected candidate will serve as a systems engineering subject matter expert responsible for guiding architecture development, requirements definition, technical evaluations, and integration activities associated with AI/ML technologies. This role requires an understanding of AI/ML concepts and their application within complex aerospace and defense systems, with a focus on evaluating technical approaches and supporting informed program decisions. The successful candidate will collaborate with government, industry, and engineering stakeholders to ensure AI/ML capabilities are effectively integrated into operational systems while supporting acquisition, test, production, and sustainment objectives.
Role and Responsibilities:
- Develop and apply systems engineering products and analyses to support the requirements, acquisition, deployment, and sustainment of unmanned aviation systems and associated autonomous capabilities.
- Support the development of AI/ML implementation strategies, concept plans, and technical roadmaps aligned with operational and program objectives.
- Define and maintain system requirements, interface definitions, and architecture products for AI/ML-enabled systems and capabilities.
- Assess, evaluate, and recommend AI/ML approaches, technologies, and architectures to support mission and operational requirements.
- Conduct technical trade studies, analyses of alternatives, and engineering assessments to inform program decisions and investment priorities.
- Coordinate with government stakeholders, development teams, test organizations, and platform integrators to support successful system implementation and fielding.
- Provide systems engineering oversight of AI/ML data management, model development, validation, integration, and deployment activities performed by technical teams.
- Support engineering investigations and deficiency analyses to identify root causes, evaluate corrective actions, and recommend technical solutions.