Forward Deployed Engineer, Energy, Megapack

What to Expect

Tesla Energy is seeking a Forward Deployed Engineer to build the software and AI that turns production problems into working systems across Megafactories, cell production, and Powerwall sites. You will own the path from a live production issue to shipped software: diagnose the problem, write the code, integrate it with factory systems, and make it stick. Time is split between the line and the desk. This is a traveling position, up to 50% of the time.

What You’ll Do

• Design, write, and ship production software: Python services, TypeScript/React tools, APIs, and data pipelines that connect cloud backends to on-prem factory systems
• Own the path from prototype to production: Git, code review, tests, CI/CD, containers, and rollback
• Turn a production problem into a working AI solution — whiteboard to deployed MVP, then harden it
• Partner with supervisors, line leads, process engineers, and site IT to translate production problems into production-grade software
• Integrate AI and factory software into live systems: APIs, auth, data hookups, logging; operate Docker, Kubernetes, and CI/CD
• Debug across systems you did not build — agents, APIs, data feeds, and network boundaries — when production is waiting
• Spend time on the line to validate the solution; build and productize at the desk
• Turn one site's working solution into a reusable playbook and feed production signal back to the product team

What You’ll Bring

• Bachelor's in Computer Science, Software Engineering, or equivalent professional experience
• 5+ years writing and shipping production software (not coursework, certs, or tutorials)
• Strong fundamentals: data structures, algorithms, systems design, debugging, and testing
• Full-stack fluency: Python on the backend; TypeScript/JavaScript on the frontend; REST APIs; SQL; Git
• A portfolio of deployed production work — GitHub, internal tools, or shipped products
• Experience operating what you build: Docker, CI/CD, and at least one of Kubernetes, Terraform, or a major cloud (AWS/GCP/Azure)
• Hands-on LLM/agent systems in production (auth, latency, evals, uptime)
• Comfort going from an unclear production problem to working software