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.
What You'll Do:
Design and implement backend services, APIs, and workflows that support autonomy development — including learning, evaluation, simulation, and operational analysis.∙Build and operate systems for orchestrating jobs and tasks across distributed environments, including containerized and clustered execution.∙Design, implement, and maintain reinforcement learning training workflows: training loop orchestration, metrics collection, checkpointing, and experiment tracking. Develop tooling and interfaces that visualize high-dimensional, time-varying autonomy data — telemetry, model outputs, learning artifacts, and simulation results.∙Approach feature development from an AI-first perspective, designing tools around how autonomy engineers reason about data, model performance, and failure modes.
Required Qualifications:
∙ 7–10 years of professional software engineering experience∙ Strong proficiency in Go and Python, with production backend experience in both.∙ Prior exposure to C++.∙ Fluency in API design, service ownership, and data modeling.∙ Experience building or operating task and job orchestration systems for ML or data workloads.∙ Deep care for developer experience and user experience when building internal platforms and tools.∙ Ability to take initiative, move quickly, and operate effectively in fast-paced environments.∙ Taste matters more than syntax — you understand system architectures deeply and use frontier AI tooling to ship faster without losing that understanding.
Preferred Qualifications:
∙ Strong understanding of reinforcement learning workflows end-to-end, preferably in robotics or autonomy contexts.∙ Experience with VLMs, VLAs, and foundation model fine-tuning pipelines (applied, not research).∙ Familiarity with JavaScript/TypeScript and React for frontend development.∙ Experience with containerized and distributed systems (Docker, Kubernetes, or similar orchestration platforms).∙ Comfort with notebook-based workflows for experimentation, analysis, and debugging.∙ Background in startups or early-stage teams, including founder or founding engineer experience.∙ Experience building visualization-heavy, analysis-oriented tooling for complex datasets.∙ Experience delivering software in constrained, secure, or operational-sensitive environments.
Principal- $222,000-$333,000Senior Staff-$185,000-$278,000Staff- $156,000-$235,000
