Staff Software Engineer, Generative AI

What to Expect
As a Staff Software Engineer on the Bottlerocket team, you will architect and operate the backend infrastructure that powers Tesla's internal Generative AI platform. You will own critical, high-throughput services end-to-end and drive technical decisions across the stack. This role demands deep systems expertise, you will be solving hard problems around concurrency, reliability, and scale in a fast-moving environment where the playbook is still being written.

What You’ll Do

• Design, build, and operate production systems that handle high-throughput, low-latency workloads at scale
• Own backend services end-to-end: from API design and data modeling through deployment, observability, and incident response
• Drive architectural decisions for complex systems involving event streaming, caching, service mesh, and workload orchestration
• Partner with ML engineers, product teams, and infrastructure teams to translate requirements into robust, scalable backend solutions
• Mentor engineers across the team, establish engineering best practices, and raise the bar for code quality and system design
• Lead capacity planning and reliability engineering to maintain high availability for business-critical services

What You’ll Bring

• 8+ years of experience building and operating production systems
• Strong, production-level proficiency in Go and Python
• Deep expertise with Kubernetes, Docker, and container orchestration in production environments
• Hands-on experience with message brokers and event streaming systems like Kafka
• Solid background with relational and analytical databases (Postgres, Click House, or similar) and caching layers (Redis)
• Strong understanding of networking fundamentals: HTTP/2, gRPC, WebSockets, TLS, and reverse proxy architectures (Envoy)
• Experience with observability stacks: Prometheus, Grafana, structured logging, and distributed tracing
• Proven experience with CI/CD pipelines, Git Ops workflows, and infrastructure-as-code (Helm, Terraform)
• Proficient in leveraging AI coding tools (e.g., Claude Code, GitHub Copilot, Cursor) to accelerate development
• Demonstrated ability to navigate ambiguity, make pragmatic tradeoffs, and deliver in environments where standards are still emerging as well as a problem-solving mindset with strong attention to detail and a preference for simple, correct solutions over clever ones