Staff Full-Stack Engineer (Forge)

Join our team as a Staff Full-Stack Engineer and help shape the future of physical AI. You will work across TypeScript and React applications, backend services, APIs, and Python data workflows. Your work will bring together internal platforms and open-source software across local and Kubernetes environments. You will own features from user needs and design through implementation, deployment, and support. This role is perfect for a generalist who enjoys moving between frontend and backend work and is curious about the systems that connect them.

Responsibilities

• Contribuer à la conception et à l'évolution des API et des modèles de données qui soutiennent les applications, l'automatisation et les intégrations avec d'autres équipes.
• Travailler directement avec les utilisateurs, les équipes produit, de conception et d'ingénierie pour définir la portée, faire des compromis pratiques et livrer des améliorations de manière itérative.
• Aider à livrer des résultats en permettant aux équipes Hivemind de compléter les workflows de développement et d'évaluation grâce à des applications cohérentes et des services fiables.
• 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

Requirements

• Familiarity with containers, CI/CD, and deploying and debugging services in a shared environment
• Proficiency with TypeScript and React, including component design, state management, asynchronous data handling, and API integration
• Experience delivering and supporting production applications, with meaningful contributions to both frontend and backend development
• 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
• Clear communication, sound engineering judgment, and the ability to work directly with users and carry work from an ambiguous problem to a supported solution
• 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

Preferred

• Practical Kubernetes experience is a plus, particularly supporting applications in cloud or on-premises environments
• 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

Pay

USD 190,000 - 290,000