Job description

ABOUT CODERABBIT CodeRabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million code reviews each week. We build the symbiotic partnership between developers and AI that makes shipping fast software safe again, reviewing every pull request, IDE change, and CLI commit so teams can move quickly without breaking things. We are a fast-moving, well-funded company, fresh off a $143M Series C at a $1.5B valuation — building Agentic Change Management, the control layer for software changes created by humans and agents. As AI writes more of the world's code, the bottleneck moves from implementation to judgment and helping human judgment scale is exactly the problem we exist to solve. 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 - Distributed Systems: queuing, eventual consistency, backpressure, graceful degradation - Infrastructure as Code: Advanced Terraform — module design, state management, programmatic provisioning patterns - Cloud Platforms: GCP (GKE, Cloud Run, VPC, IAM, Cloud SQL, Cloud Storage, Load Balancing) — how these work under the hood, not just how to configure them - Programming: Node.js/TypeScript or Go for platform tooling, operators, and automation - Observability: Datadog, Prometheus/Grafana or equivalent — custom instrumentation, distributed tracing, SLO-based alerting - Systems: Linux internals, networking fundamentals (TCP/IP, DNS, load balancing, eBPF), storage systems Why Join Our Engineering Culture? - CodeRabbit is building the next generation of AI-native developer tooling; starting with code review. We combine large language models with deep software engineering context to help teams ship faster, catch more bugs, and make better architectural decisions at scale. - We have a high-ownership engineering culture. That means no passive execution, no waiting for perfect tickets, and no narrowly defined task boundaries. Engineers here find problems before they're assigned, use AI as a core part of how they build, ship with judgment, and own outcomes from proposal to production. - Our operating philosophy: bias toward action, ship the smallest necessary coherent slice, validate proportional to risk, watch what happens, and make the system better. AI drafts; humans decide. Speed matters, but so does understanding what you ship. - This opportunity will be energizing for people who want real ownership, pace, and high standards. It's uncomfortable for people who prefer slow consensus or heavily managed workflows. - If you want to build tools that are changing how software gets written, and be held to the standard that the best engineers thrive under; we'd love to talk. Our Values 🤝 Collaborative Humans: Prioritizing collective intelligence 🚀 Fearless Innovators: Turning obstacles into growth opportunities 💪 Persistent, Passionate Developers: Thriving on complex, long-term challenges 🎯 Impact-Driven Creators: Crafting intuitive tools for developers 🧠 Rapid Learners and Un-learners: Adapting quickly in our fast-paced technological world

Requirements

Must-haves

7+ years in Platform Engineering, Infrastructure Engineering, or Site Reliability Engineering with a strong bias toward building platforms, not just operating them
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
Distributed Systems: queuing, eventual consistency, backpressure, graceful degradation
Infrastructure as Code: Advanced Terraform — module design, state management, programmatic provisioning patterns
Cloud Platforms: GCP (GKE, Cloud Run, VPC, IAM, Cloud SQL, Cloud Storage, Load Balancing) — how these work under the hood, not just how to configure them
Programming: Node.js/TypeScript or Go for platform tooling, operators, and automation
Observability: Datadog, Prometheus/Grafana or equivalent — custom instrumentation, distributed tracing, SLO-based alerting
Systems: Linux internals, networking fundamentals (TCP/IP, DNS, load balancing, eBPF), storage systems
Why Join Our Engineering Culture?
This opportunity will be energizing for people who want real ownership, pace, and high standards. It's uncomfortable for people who prefer slow consensus or heavily managed workflows.
If you want to build tools that are changing how software gets written, and be held to the standard that the best engineers thrive under; we'd love to talk.

Nice-to-haves

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Keywords to mirror

aigcprestkubernetesawsdockersqlnode.jstypescriptgo

Platform: ashby
Effort: quick

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