Site Reliability Engineer

ABOUT CODERABBIT CodeRabbit is an innovative research and development company focused on building extraordinarily productive human-machine collaboration systems. Our primary goal is to create the next generation of Gen AI-driven code reviewers: a symbiotic partnership between humans and advanced algorithms that significantly outperforms individual engineers. We combine language models with human ingenuity to push the boundaries of software development efficiency and quality. THE ROLE We are seeking an experienced Site Reliability Engineer to join our Platform Engineering team in the Bay Area. You'll be instrumental in ensuring the high availability, performance, and scalability of CodeRabbit's AI-powered code review platform. This role sits at the intersection of software engineering and systems operations, where you'll build the foundational platforms and automation that enable our engineering teams to deploy, monitor, and scale our services reliably. As an SRE at CodeRabbit, you'll be responsible for enhancing the reliability of our critical services that process millions of code reviews, building sophisticated automation platforms, and owning the infrastructure that powers our AI-driven analysis engine. You'll work with cutting-edge technologies including large language models, real-time processing systems, and distributed architectures that operate at significant scale. KEY RESPONSIBILITIES INFRASTRUCTURE & PLATFORM OWNERSHIP - Design, implement, and maintain scalable infrastructure on Google Cloud Platform to support CodeRabbit's growing user base and processing demands - Own and operate critical platform services - Build and maintain Infrastructure as Code using Terraform to ensure consistent, reproducible, and version-controlled infrastructure deployments RELIABILITY & PERFORMANCE ENGINEERING - Establish and maintain SLI/SLO frameworks for all critical services, ensuring we meet our reliability commitments to users - Implement comprehensive monitoring, alerting, and observability solutions using Datadog and custom instrumentation - Conduct thorough incident response, root cause analysis, and post-mortem processes to continuously improve system reliability - Optimize application and infrastructure performance to handle millions of pull request analyses with minimal latency - Design and implement chaos engineering practices to proactively identify and resolve system weaknesses AUTOMATION & DEVELOPER EXPERIENCE - Develop self-service platforms and tooling that empower engineering teams to deploy, monitor, and troubleshoot their services independently - Automate operational tasks including scaling, backup/recovery, security patching, and routine maintenance - Create and maintain infrastructure APIs and abstractions that simplify complex operations for development teams SECURITY & COMPLIANCE - Integrate security best practices into all infrastructure and platform services - Implement and maintain security monitoring, vulnerability scanning, and compliance reporting - Design secure network architectures including VPC configuration, firewall rules, and access control systems - Establish and maintain disaster recovery procedures and business continuity planning REQUIRED QUALIFICATIONS EXPERIENCE & BACKGROUND - 6-8 years of hands-on experience in Site Reliability Engineering, Platform Engineering, or DevOps Engineering roles - Proven track record of managing production systems at scale, preferably in high-growth technology companies - Experience with cloud platforms, particularly AWS or Google Cloud Platform (GCP), including compute, storage, networking, and managed services - Strong background in containerization and orchestration platforms (Kubernetes, Docker) TECHNICAL SKILLS - Programming Languages: Proficiency in Node.js and TypeScript for building automation tools, monitoring solutions, and platform services - Infrastructure as Code: Advanced experience with Terraform for infrastructure provisioning and management - Monitoring & Observability: Hands-on experience with Datadog or similar platforms (Prometheus, Grafana, ELK stack) for observability - Cloud Platforms: Comprehensive experience with GCP services including Compute Engine, GKE, Cloud Run, Cloud SQL, Cloud Storage, Load Balancing, and IAM SYSTEMS & OPERATIONS - Strong Linux/Unix systems skills - Experience with network protocols, load balancing, and CDN technologies - Knowledge of security principles and best practices for cloud infrastructure - Familiarity with CI/CD tools and practices (Jenkins, GitLab CI, GitHub Actions) - Understanding of microservices architecture and distributed systems principles PREFERRED QUALIFICATIONS - Experience with AI/ML infrastructure and tools - Background in managing high-traffic web applications and API services - Experience with disaster recovery planning and execution - Familiarity with compliance frameworks (SOC 2, I