Site Reliability Engineer

HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers don't just communicate - they make decisions, take action, and run operations autonomously across voice, email, and enterprise systems. Born in Y Combinator (S23) and backed by a16z and Base10 with over $60M raised, we power critical operations for global enterprises worldwide.

Our platform is battle-tested in the most demanding environments - where AI has real consequences. We started in logistics, built our own voice stack, models, and orchestration layer from the ground up, and are now bringing that infrastructure to every enterprise that runs the real economy. Learn more about our vision in our manifesto.

We're looking for a Site Reliability Engineer to take the lead on scaling our operational resilience as we grow. You’ll own the stability, observability, and debugging workflows that keep our systems running smoothly. You'll be the go-to person for untangling complex failures in real time, designing tools that turn chaos into clarity, and helping us shift from reactive to proactive operations.

This is a high-impact, high-trust role where you’ll shape how reliability is done - reducing incident load, building internal tooling, and directly improving developer focus and system uptime. If you love getting to the root of hard problems and making systems (and teams) stronger, this is your moment.

• 4+ years of hands-on experience debugging production systems (logs, traces, incidents, etc.)

• Strong problem-solving skills and ability to dive into unfamiliar backend codebases

• Strong Go and Kubernetes experience.

• Familiarity with observability and monitoring tools (e.g., Grafana, Prometheus, Sentry)

• Clear, calm communication under pressure — especially during live incidents

   

• Experience working with distributed systems or services at scale

• Built or maintained internal tooling for on-call teams or reliability workflows

• Familiarity with deployment pipelines, CI/CD, or infra-as-code

• Experience improving system observability (e.g., custom metrics, traces, log pipelines)