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Shield AI is a venture-backed defense-tech company building autonomy systems for air, maritime, space, and other platforms in complex and contested environments. Forge is the engineering platform that connects autonomy developers with applications, services, compute, data, and workflows needed to move from local development to deployed systems.
You will be a full-stack engineer shaping the future of physical AI by building tools to develop, train, and validate autonomous systems. Working across TypeScript and React applications, backend services, APIs, and Python data workflows, you will emphasize extensibility and reuse. Your work will integrate internal platforms and open-source software across local and Kubernetes environments.
Key responsibilities include:
- Build complete features across React interfaces, backend services, APIs, and data storage
- Translate complex technical workflows into intuitive applications with clear progress, results, and useful failure investigation paths
- Design and evolve APIs and data models supporting applications, automation, and integrations with other teams
- Contribute to platform and application architecture through requirements or direct contribution
- Build software that runs across local workstations, CI/CD, and air-gapped Kubernetes clusters
- Test and support your work using logs, metrics, traces, and user feedback to improve reliability, performance, and usability
- Work directly with users, product, design, and engineering teams to define scope, make tradeoffs, and deliver improvements iteratively
You will own features from user needs and design through implementation, deployment, and support. Working directly with Hivemind Pilot developers, Hivemind Solutions teams, and domain experts, you will translate complex workflows into reliable applications and reusable services. 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.
Key outcomes include enabling Hivemind teams to complete development and evaluation workflows through coherent applications and dependable services; ensuring features work reliably across supported environments with clear diagnostics; enabling other teams to integrate with and extend Forge through documented APIs and reusable components; and making changes straightforward to test, deploy, maintain, and support.
REQUIREMENTS:
- Experience delivering and supporting production applications with meaningful contributions to both frontend and backend development
- Proficiency with TypeScript and React, including component design, state management, asynchronous data handling, and API integration
- Experience building backend services in Go, Python, or comparable language, including API design, validation, and error handling
- Experience working with databases and application data models, including querying, persistence, and schema changes
- Ability to reason about service interactions, authentication, authorization, background jobs, and failures across application boundaries
- Familiarity with containers, CI/CD, and deploying and debugging services in a shared environment
- Clear communication, sound engineering judgment, and ability to work directly with users and carry work from ambiguous problems to supported solutions
PREFERRED QUALIFICATIONS:
- Hands-on Kubernetes experience deploying or troubleshooting applications, including Helm charts, service configuration, networking basics, and persistent storage
- Developer tools or technical applications for simulation, experimentation, training, test and evaluation, or deployment
- Job orchestration, distributed execution, or data-processing workflows using Ray, Kubernetes Jobs, Argo Workflows, or Dagster
- Schema-driven APIs, generated clients, or service integrations using OpenAPI, JSON Schema, Protocol Buffers, gRPC, or WebSockets
- Extensible applications, plugin systems, shared component libraries, or AI-assisted workflows and agent-tool integrations
- Applications deployed across cloud, on-premises, edge, or air-gapped environments; familiarity with robotics, autonomy, or simulation
