Sustainment Technical Product Specialist

Title: Sustainment Technical Product Specialist Belong. Connect. Grow. with KBR! KBR’s National Security Solutions team provides high-end engineering and advanced technology solutions to our customers in the intelligence and national security communities. In this position, your work will have a profound impact on the country’s most critical role – protecting our national security. KBR (formerly LinQuest) is the prime contractor on the Military Satellite Communications (MILSATCOM) Systems Engineering, Integration and Test (MSEIT) contract. KBR is seeking a highly-skilled, motivated and proactive teammate to support Mission Delta 8 (MD8), 8th Sustainment Squadron (8STS) located at Peterson Space Force Base (PSFB), CO. We conduct operations and sustainment (O&S) activities for state-of-the-art Military and Commercial Satellite Communications (SATCOM) and Nuclear Command, Control and Communications (NC3) systems, providing global secure, survivable and protected communications for our Nation’s warfighters. We are looking for an experienced, dynamic and effective Sustainment Technical Product Specialist for a front-facing role within the Government System Program Office to effectively develop and implement Artificial Intelligence (AI) and Machine Learning (ML) solutions across the MILSATCOM & NC3 O&S portfolio. The ideal candidate will bring their innovative skills and passion to identify where AI-enabled workflows can bring measurable value to the portfolio, prototype those capabilities using modern tools and repeatable workflows, and build the evaluation and verification discipline needed to make those capabilities trustworthy for fielding. The role spans the full capability lifecycle: discovering relevant mission use cases, building practical prototypes and evaluation assets, assessing operational fitness and failure modes, and transferring knowledge to the broader engineering team through documentation, briefings, and mentoring. This position is intentionally scoped to reflect a high-autonomy engineer who can independently research emerging practices, convert learning into usable artifacts, and align AI capability development with mission needs, engineering rigor, and leadership decision-making. This position will be joining our high-functioning, high-performing MSEIT Sustainment IPT and be an important part of directly and positively affecting warfighter readiness as they employ US Space Force (USSF) systems worldwide in support of full spectrum military operations. Why Join Us? Innovative Projects: KBR’s work is at the forefront of engineering, logistics, operations, science, program management, mission IT and cybersecurity solutions. Collaborative Environment: Be part of a dynamic team that thrives on collaboration and innovation, fostering a supportive and intellectually stimulating workplace. Impactful Work: Your contributions will be pivotal in designing and optimizing defense systems that ensure national security and shape the future of space defense. Key Responsibilities Duties and Responsibilities include, but are not limited to: • Develop and maintain a practical roadmap for agentic AI and AI/ML evaluation capabilities that can be applied to the MSEIT Sustainment Test and Evaluation effort • Conduct structured applied learning in AI/ML, LLMs, RAG, agents, evaluation frameworks, tracing, safety, reliability, and related software practices; convert learning into usable artifacts • Design, build, and maintain evaluation harnesses for LLM-enabled and agentic AI applications, including golden test sets, rule-based and model-based graders, human-validated scoring approaches, CI-integrated regression gates, and evidence packages • Define evaluation claims, measures, acceptance criteria, datasets, rubrics, test conditions, traces, and readiness evidence for AI-enabled systems • Evaluate not only what an AI system says, but what it does, how it does it, what authority it exercises, and what happens when it deviates • Instrument AI systems with distributed tracing and observability practices to support failure diagnosis, drift detection, regression analysis, and black-box evaluation in constrained environments • Conduct adversarial and resilience-oriented assessments of agentic systems, including prompt injection, goal hijacking, tool misuse, memory poisoning, and related failure modes; document findings and mitigation outcomes • Help distinguish AI-system failure from test-case defects, evaluator defects, environment failures, configuration problems, and insufficient evidence • Translate reproducibility, auditability, evaluation integrity, resilience, operational recovery, safety assurance, and human oversight into testable engineering requirements and practical contract guidance • Map established T&E practices to AI evaluation and create roadmaps, playbooks, demonstrations, templates, and guidance that help other engineering and test personnel extend their skills into the AI domain • Identify mission-relev