Senior Full-Stack Engineer (Forge)

• 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
• 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:
• A successful engineer in this role will help deliver the following 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

Benefits

• Excellent Medical Coverage
• Mental Health Employee Assistance Program
• Paid Parental Leave
• Pet Insurance
• Flexible Work Hours
• Onsite Gym (DC)
• Gym Discount (San Diego)
• Free Parking
• Competitive Compensation
• Stock Benefits
• 401K Services and Match- Experience building backend services in Go, Python, or a comparable language, including API design, validation, and error handling
• Experience delivering and supporting production applications, with meaningful contributions to both frontend and backend development
• 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
• Proficiency with TypeScript and React, including component design, state management, asynchronous data handling, and API integration
• Ability to reason about service interactions, authentication, authorization, background jobs, and failures across application boundaries
• Experience working with databases and application data models, including querying, persistence, and schema changes
• 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
• 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
• Schema-driven APIs, generated clients, or service integrations using OpenAPI, JSON Schema, Protocol Buffers, gRPC, or WebSockets