Senior/Staff Platform Engineer

About the role

ABOUT CODERABBIT

CodeRabbit is the governance and control layer for agentic software development, helping engineering teams trust the code they ship. AI can generate code faster than people can review and understand it. Teams still need to know whether each change solves the right problem, fits their architecture, and is safe to ship.

We provide independent validation grounded in codebase context and team standards, giving people the evidence they need to judge what should ship. Across Review, Triage, Explain, and Secure, our platform challenges changes before merge, prioritizes pull requests by value, impact, and risk, explains what changed and why it matters, and monitors the codebase for security vulnerabilities after merge.

CodeRabbit serves nearly 20,000 customers and supports approximately 300,000 open-source repositories, performing over 2 million code reviews each week. Our $143M Series C, raised at a $1.5B valuation, supports further product development and international expansion.

About the Role

CodeRabbit is hiring its founding Platform Engineer. You'll own the compute, orchestration, and infrastructure layer that CodeRabbit's AI engine and every product on top of it run on, across a multi-region GCP footprint and a product suite that's still growing. This is a 0-to-1 role: you'll build the platform function from the ground up, set the technical direction, establish the patterns everyone else builds on, and make the early architectural calls that are expensive to unwind later. This role carries the same ownership and pace as the rest of CodeRabbit engineering, applied with the rigor that foundational infrastructure demands. The systems you build here need to be right, not just fast — everything else depends on them.

Required Qualifications

- 7+ years in Platform Engineering, Infrastructure Engineering, or Site Reliability Engineering with a strong bias toward building platforms, not just operating them

- Deep, hands-on experience with Kubernetes: you've gone beyond running workloads to understanding and configuring the control plane, writing operators or controllers, tuning schedulers, and debugging at the runtime level; bonus if you've contributed to Kubernetes or built on its internals

- Experience building and running large-scale distributed systems. You understand the trade-offs between consistency and availability, have debugged distributed failures in production, and have designed systems around them

- Strong cloud compute background on GCP or AWS. You've built infrastructure, not just consumed managed services; you understand how compute, networking, and storage primitives work at the layer below the console

- Proficiency in Docker and container runtime internals: image layering, networking modes, security contexts, and build optimization

Technical Skills

- Container & Orchestration: CRDs, operators, admission webhooks, RBAC, network policies, autoscaling; strong Docker/OCI toolchain knowledge