SETA Systems Engineer - AI focus (2026-0174)
Acclaim Technical Services · Mclean, VA
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Jul 27, 2026
Mclean, VA
Jul 28, 2026
What this job asks for AI summary
A systems engineering role with an AI focus supporting a U.S. Federal intelligence community client in McLean, VA. The position involves integrating AI research and development prototypes, applying systems engineering principles to government R&D programs, and engaging with frontier AI research. It suits candidates with a strong academic background in AI and prior national security sector experience.
Senior level · 5+ years · Washington-Arlington-Alexandria, DC-VA-MD-WV · Master's required · TS/SCI clearance
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Why we read it this way (7)
The SOC classification is uncertain: the role blends systems engineering, AI research, and government R&D program support without a clear primary technical occupation. 15-1299 (Computer Occupations, All Other) is used as the best fit; 15-2051 (Data Scientists) is a plausible alternative given the AI/ML research emphasis.
The posting requires a Master's degree or PhD in AI or a closely related field — a Bachelor's is not listed as an acceptable minimum, so Master's is set as the degree floor.
The TS/SCI with Full Scope Polygraph (FSP) is explicitly required ('active TS/SCI FSP'), mapped to TopSecretSci.
All skills listed are either domain concepts (AI, systems engineering) or methodologies (project management, system integration) rather than named tools or platforms. No specific software, frameworks, or technologies are mentioned anywhere in the posting.
The 'Desired Qualifications' section is framed as preferred/desired throughout, so those skills are marked accordingly. The 5+ years of AI experience and national security sector experience appear in the 'Ideal candidate' block with firm language and are treated as hard gates.
Ignored 2 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): Systems Engineering, Project Management.
Requires a TS/SCI clearance — the cleared population is a small fraction of this occupation, so the real candidate pool is materially smaller than the estimate below, which does not model clearance.
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