AI Implementation Engineer, HQ CFC S357/S35A

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The United States Space Force (USSF) at Peterson SFB, Colorado Springs, CO is searching for an AI Implementation Engineer, to support HQ CFC S357/S35A (NH-1560-03, GS-12/13 Equivalent).

Description: Are you a data scientist who wants to build combat capabilities, not just reports?

The USSF's Combat Forces Command (CFC) is looking for an action-oriented Data Scientist to join our front-line team.

You will work directly with space warfighters, find their hardest problems, and deliver the AI-driven solutions that solve them.

This is not a back-office analytics job; you will work with our operators, deploy solutions at the speed of relevance and proving their effectiveness in the real world.

We are a small, elite team with a single purpose: free our Guardians to focus on the attack. We forge the AI-driven capabilities that give our Guardians a decisive overmatch.

We are looking for practitioners who thrive on challenge and want to see their work make a real difference in national security.

Ideal Candidate: The ideal candidate is a hands-on technical expert focused on delivering combat capability.

They are a mission-driven, self-starting data scientist who thrives on solving complex operational problems with data and AI-enabled solutions.

They must possess expert knowledge of data science and software engineering, demonstrated through a history of rapidly prototyping and fielding solutions for mission problems (AI/ML models and applications preferred).

This is a role for a practitioner, not a theorist. This position directly drives our ability to maintain decision superiority.

Background: Experience and knowledge must demonstrate the ability to translate ambiguous warfighter needs into functional software.

This includes advanced proficiency in Python and leading ML frameworks, coupled with expert skill in building and managing DevSecOps data pipelines.

A deep understanding of how to rigorously test, validate, and verify AI systems in real operational environments is paramount.

Candidates will advise command leadership on complex technical subjects, serving as a critical liaison to other DAF, DOW, and external acquisition partners on AI integration for space warfighting.

Direct partnership with operators in tactical environments is a continuous expectation.

Experience in the space domain is highly desired, but a proven record of shipping high-impact software solutions that deliver decisive overmatch is paramount. Key Skills and Abilities: 1.

Expert knowledge of Data Science and Machine Learning.

The candidate must be able to articulate and defend their preferred methodologies for applying advanced statistical analysis and algorithm development to solve ambiguous, real-world operational problems.

They must demonstrate a deep understanding of the trade-offs between different AI/ML approaches (e.g., deep learning vs. classical ML, supervised vs.

unsupervised) and justify their choices based on mission requirements. 2. Expert skill in Mission-Focused Software Engineering.

The candidate must describe their proven process for translating complex models into production-grade, maintainable, and deployable software applications.

They must be prepared to discuss their philosophy on writing clean code, building robust systems, and validating that software is ready for a demanding military environment. 3.

Skill in building and commanding a modern DevSecOps infrastructure.

This requires demonstrated, hands-on experience designing and implementing automated data pipelines and full-stack CI/CD workflows in a cloud or hybrid-cloud context.

The candidate must be a practitioner capable of building the entire "digital arsenal" from the ground up, including secure containerization and orchestration (Docker/Kubernetes). 4.

Ability to execute under pressure at the tactical edge.

The candidate must possess the skill to take a vaguely defined warfighter need, rapidly translate it into a minimum viable product (MVP), and then iteratively improve that product based on direct, and often blunt, operator feedback in high-stress, time-sensitive operational and exercise environments.

5. Ability to prove combat effectiveness through rigorous Test & Evaluation. The candidate must have skill in designing and implementing robust testing and validation plans for complex AI systems.

This includes knowledge of operational testing, bias detection, fairness assessment, and explainability techniques required to build warfighter trust and formally verify a capability's lethality. 6.

Ability to drive strategic decisions with technical clarity. The candidate must have the skill to distill highly technical information into concise, "plain English," mission-focused recommendations.

They must be able to confidently advise General Officers and other senior leaders on the operational risks and opportunities presented by AI, directly influencing command-level strategy.