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 RoleWe 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.
What you'll do:
- 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 paths to investigate failures.
- Design and evolve APIs and data models that support applications, automation, and integrations with other teams.
- Contribute to a platform / application architecture directly through requirements or direct contribution.
- Contribute to software that is meant to run in a multitude of environments from local workstations, to CICD, to airgapped Kubernetes clusters.
- Test and support what you build, 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 practical tradeoffs, and deliver improvements iteratively.
Key outcomes:
- Hivemind teams can complete development and evaluation workflows through coherent applications and dependable services.
- Features work reliably across supported local and cluster environments, with clear diagnostics when something goes wrong.
- Other teams can integrate with and extend Forge through documented APIs and reusable components.
- Changes are straightforward to test, deploy, maintain, and support as the platform evolves.
Required qualifications:
- 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 a 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 the ability to work directly with users and carry work from an ambiguous problem to a supported solution.
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 tools such as 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.
Why join us:
- Own complete solutions. Shape the user experience, implement the services behind it, and see your work through deployment and real use.
- Build software with direct mission impact. Help engineers develop, validate, and deliver autonomy capabilities more effectively.
- Work alongside engaged users. Partner with autonomy, ML, and simulation experts and see how your decisions affect their daily work.
- Influence a growing platform. Turn practical application needs into shared capabilities that benefit teams across Hivemind, including new AI-assisted engineering workflows.
Skills Required
- Experience delivering and supporting production applications with meaningful frontend and backend contributions
- Proficiency with TypeScript and React, including component design, state management, asynchronous data handling, and API integration
- Experience building backend services in Go, Python, or a 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 shared environments
- Clear communication, sound engineering judgment, and ability to carry work from an ambiguous problem to a supported solution
- Hands-on Kubernetes experience, including Helm charts, service configuration, networking basics, and persistent storage
- Experience with developer tools or technical applications for simulation, experimentation, training, test and evaluation, or deployment
- Experience with job orchestration, distributed execution, or data-processing workflows using Ray, Kubernetes Jobs, Argo Workflows, or Dagster
- Experience with schema-driven APIs, generated clients, or service integrations using OpenAPI, JSON Schema, Protocol Buffers, gRPC, or WebSockets
- Experience with extensible applications, plugin systems, shared component libraries, or AI-assisted workflows and agent-tool integrations
- Experience deploying applications across cloud, on-premises, edge, or air-gapped environments; familiarity with robotics, autonomy, or simulation
What the Team is Saying
Shield AI Compensation & Benefits Highlights
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Healthcare Strength — Company materials highlight comprehensive medical, dental, and vision coverage with mental-health support and an EAP. Third-party benefits summaries also portray health coverage as a strong component of the package.
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Retirement Support — Offerings include a 401(k) with employer matching, cited on the careers page and independent benefits directories. Multiple sources indicate a match exists, though exact formulas have varied over time and warrant confirmation.
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Equity Value & Accessibility — Company communications describe equity for all full-time hires and stock benefits as part of total rewards. Independent listings also note company equity/RSUs as a standard element.
Shield AI Insights
What We Do
At Shield AI, you won't wait years to see your work reach the field. You'll build hardware and software that operates in the real world right now, in the hands of the people who depend on it. Hivemind, our AI pilot, has been flying since 2018. It has flown more than 30 platforms, including an F-16, and it now sits under a U.S. Air Force production contract for Collaborative Combat Aircraft. When you write code or shape a system here, you contribute to technology with a proven flight record and a clear production future. V-BAT flies intelligence, surveillance, and reconnaissance missions with an operational record that stretches from Ukraine to the Indo-Pacific. It delivers eyes where they matter most, in the most demanding conditions on earth. The teams behind it watch their work get tested where the stakes are real. X-BAT takes its first flight this year. It's an AI-piloted fighter that needs no runway, built to operate where traditional aircraft can't. Join now and you help shape a program at its earliest, most formative stage. That's the kind of ground-floor work that defines a career. Do the most impactful work of your life, on problems that matter. Autonomy at this level asks a lot of you. You'll take on problems in perception, planning, and control that few teams anywhere are equipped to solve. You'll work across disciplines, from aerospace and robotics to machine learning and systems engineering, alongside people who hold themselves to an exacting standard and expect the same from you. Our mission is clear: protect service members and civilians with intelligent systems. That purpose runs through every decision, every design review, and every deployment. It's why the work here carries a weight you can feel. Ready to join our mission? Explore our open roles and find where you fit.
Why Work With Us
Founded in 2015 by a former Navy SEAL, Shield AI builds AI pilots and uncrewed aircraft. Veterans aren't an afterthought here, they're at every level. It's why the work carries weight: AI pilots and uncrewed aircraft flying real missions, from Ukraine to the Indo-Pacific, protecting service members and civilians.
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Hybrid Workspace
Employees engage in a combination of remote and on-site work.
