Design 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

We're looking for a Design Engineer who lives at the intersection of design and code. You will prototype, build, and polish the experiences that make CodeRabbit feel like a trusted teammate rather than noise — across IDEs, Git platforms, the CLI, and the web, surfaces with few established conventions, where the right interaction pattern hasn't been invented yet.

Whether a developer trusts an AI-generated suggestion enough to merge it often comes down to execution: the pixels, the motion, the copy, the milliseconds of latency, the edge cases. This role owns that last mile. It is perfect for someone who thinks like a designer but builds like an engineer — or vice versa.

This is a high-ownership role working directly with design, engineering, and AI teams to define what's possible and then ship it, fast.

WHAT YOU'LL DO

- Build production-quality UI. Ship polished components and interactions that make complex code analysis feel effortless and earn developers' trust in AI-generated suggestions.

- Prototype rapidly. Turn concepts for emerging AI experiences — real-time review, conversational feedback, agentic workflows — into working prototypes in hours, not days, to validate ideas before full implementation.

- Bridge design and engineering. Translate high-fidelity designs into pixel-perfect code, and push design forward through technical innovation the mockups couldn't anticipate.

- Own implementation quality. Set and hold the bar for UI execution across the product — smooth interactions, thoughtful motion, and micro-interactions that make the product feel alive.

- Build the design system in code. Create and maintain reusable, well-engineered components spanning Web, IDE extensions, Git platforms, and CLI surfaces, so the whole team ships faster.

- Make complex data legible. Implement clear, performant visualizations for code quality metrics, dependency graphs, and AI-generated insights.