Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices and facilities across the U.S., Europe, the Middle East, and the 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.

The Platform Applications team builds the tools, services, and workflows that autonomy engineers at Shield AI depend on daily. This is where training gets orchestrated, simulations get analyzed, and high-dimensional data becomes something a human can actually reason about.
You’ll own production systems end-to-end — backend services, APIs, orchestration layers, and the visualizations and interfaces that make it all usable. The work spans reinforcement learning pipelines, distributed job execution, and developer tooling for teams working with VLMs, VLAs, and foundation model fine-tuning — not building foundational models, but building the platform that lets domain experts train, evaluate, and deploy them.
This is hands-on, high-ownership work. You’ll shape how engineers interact with data, training runs, simulation orchestration, and evaluation outputs across the platform. It’s a good fit for someone who cares deeply about craft, thinks in systems, and wants to see their tools used in the real world — literally in the field, supporting real defense operations.
We work in small, fast-moving teams. If you’re the kind of engineer who builds things on weekends because you find it genuinely interesting, who uses AI-native development workflows (Claude Code, Codex, agentic tooling) to iterate fast while maintaining a deep understanding of the architectures underneath — we want to talk to you.