About the role
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. Role Overview As a Software Engineer at CodeRabbit, you'll be contributing to the development of advanced applied AI systems that revolutionize code review processes. You'll work at the intersection of intelligent systems and software engineering, creating tools that empower developers to iterate rapidly in complex environments. Your expertise will be crucial in developing solutions that enhance code quality, scalability, and developer productivity. You’ll help architect and build core backend systems — the infrastructure that powers our AI agent workflows, context-enriched code reviews, repo-level planning tools, and dashboard interfaces. You’ll work alongside AI researchers, infra specialists, frontend engineers, and product thinkers to build reliable, intelligent backend systems that power our developer tools at scale.
Responsibilities Architect and build scalable backend services, APIs, and distributed systems Collaborate with ML engineers to integrate models into agent-based systems and AI products involving autonomous or task-driven agents Guide junior engineers through mentorship and technical reviews Own architectural decisions in new product features Ensure reliability, performance, and security across systems Contribute to an engineering culture of speed, quality, and pragmatic innovation
Qualifications Education : Degree in Computer Science, Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience Experience : 3 - 5 years of experience building backend systems and distributed infrastructure Technical Expertise : Fluency in TypeScript and Node.js, or a similar modern backend stack; experience with microservices, async job queues, and event-driven architectures Systems Thinking : Familiarity with cloud platforms (AWS/GCP), containerization (Docker/Kubernetes), CI/CD pipelines, devops tooling, runtime infrastructure, and production observability Engineering Craft : Strong understanding of software engineering best practices, including testing, code reviews, and version control workflows Product Mindset : Thoughtful about trade-offs, user experience, and fast iteration Team Leadership : Willing to mentor, lead by example, and influence technical direction without being a pure manager
