Shield AIPosted 2mo ago

Staff Engineer, AI Factory (R5276)

Staff Engineer, AI Factory (R5276) at Shield AI scores 28 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.

Washington, D.C.leadFull Time Employee$150k-$220k

AI in this role

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.

Job Description:

As a Software Engineer on the HMS Factory Team, you will develop, implement, and maintain the automated testing frameworks, log analysis tools, and scenario-generation scripts built on top of the Hivemind Platform (HMP) SDK. Your work is highly technical and hands-on, directly enabling hundreds of autonomy and systems developers to rapidly verify AI Pilot behaviors across our expansive portfolio set. In this role, you will navigate complex environment boundaries between secure GovCloud and commercial ecosystems, tackling deep build-system challenges such as dependency migrations and establishing reliable artifact and source-mirroring pipelines across isolated networks.

You will write python-based analytics libraries, build custom wrappers around the HMP Forge test orchestrator, and programmatically generate complex testing environments using domain randomization. You will also participate in the hands-on prototyping and deployment of new distributed testing technologies like on top of the Forge Server to support massive batch-testing runs. Additionally, you will serve as a critical technical bridge, translating raw simulation telemetry into structured, high-fidelity insights while keeping mainline branches unified and stable in the face of varying program upgrade cadences.