Software Engineer, Fleet Management

Job description

What to Expect Tesla builds fleet management and robot control software that orchestrates autonomous robots and automation systems — including AMRs, ASRS and conveyance systems — across global manufacturing and warehouse facilities. The platform integrates with robots, industrial equipment, and internal MES systems to coordinate material flow end-to-end. These systems are production-critical and directly impact factory throughput, uptime, and scalability. We are seeking a Software Engineer to join the Fleet Management team. The team is embedding AI agents into the platform across agent-assisted support for factory operators, automated response to production incidents, and AI-driven robot orchestration. You will spend the majority of your time on the TypeScript agent stack, while also shipping Go fleet-platform changes and the operator-facing tools that make those agents usable on the factory floor. You will work within a small, focused team alongside a Staff-level domain lead and experienced engineers. You will receive mentorship on agent development and systems design while being expected to take ownership of meaningful features from day one. This position is based in Austin, TX (onsite). What You’ll Do Own agent features across the TypeScript agent stack and the Go fleet platform — including tool calling, prompt and skill design, workflow orchestration, and the APIs those agents call Build agent-assisted workflows that help factory operators and support engineers diagnose fleet issues and act on them Automate incident response with agents that detect, triage, and assist in resolving production incidents Explore and apply LLM and ML techniques to job scheduling, vehicle routing, anomaly detection, and fleet decision-making Define how we measure agent quality — evals, golden test cases, scoring pipelines, and cost observability Contribute to frontend tooling that gives factory operators agent-assisted workflows and visibility into fleet status Write tests and instrumentation that make agent and fleet behavior transparent and debuggable What You’ll Bring Bachelor's Degree in Computer Science or a related field, or equivalent experience Strong foundations in algorithms, data structures, and systems design Proficiency in TypeScript or Go — interest in working across the agent stack, fleet backend, and operator UI Exposure to LLM application development including agents, tool or function calling, and prompt engineering — familiarity with agent frameworks such as Mastra and agent UI libraries such as CopilotKit is a plus Working familiarity with React, GraphQL, and Docker — Kubernetes experience is a plus Deep interest or experience in AI agents, robotics, fleet management, logistics, or automation Product-minded — you think about the operators behind the screen and how they will use what you build Extracted Data Skills: TypeScript, React, Docker, Kubernetes, Robotics Education: Bachelor's