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.
About Shield AI
Shield AI is a defense technology company with the mission of protecting service members and civilians with intelligent systems. We build autonomy systems for air, maritime, space, and other platforms operating in complex and contested environments.
Forge is the engineering platform used to build, integrate, test, and operate Hivemind capabilities. It connects autonomy developers with the applications, services, compute, data, and workflows they need to move from local development to deployed systems.
The Role
We are looking for a full-stack engineer to help shape the future of physical AI by building tools to develop, train, and validate autonomous systems. You will work across TypeScript and React applications, backend services, APIs, and Python data workflows, with an emphasis on extensibility and reuse. Your work will bring together internal platforms and open-source software across local and Kubernetes environments.
You will build Forge capabilities for simulation, synthetic data generation, training, and test and evaluation, helping engineers turn ideas into proven autonomy capabilities. Working directly with Hivemind Pilot developers, Hivemind Solutions teams, and domain experts, you will translate complex workflows into reliable applications and reusable services. You will own features from user needs and design through implementation, deployment, and support.
This role suits a generalist who wants meaningful ownership, enjoys moving between frontend and backend work, and is curious about the systems that connect them. You will help shape technical decisions and deploy and troubleshoot containerized services alongside platform engineers. Practical Kubernetes experience is a plus, particularly supporting applications in cloud or on-premises environments.
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