active · Approximate location

Senior Engineer, Full-Stack - Forge (R6244)

shieldai·San Diego, California

San Diego, California

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AT A GLANCE

Hivemind Enterprise DivisionSenior

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People Leadership

Preferred qualifications are helpful, not automatic disqualifiers.

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About the role

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.

Responsibilities

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.

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 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.
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.

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Statusactive

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