Senior Applied AI 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.

ROLE OVERVIEW

As an Applied Gen AI Engineer at CodeRabbit, you'll play a central role in designing, building, and deploying advanced generative AI systems that power our code review and developer productivity tools. You’ll be responsible for bringing the latest advancements in generative AI to life — integrating techniques like RAG, RLHF, and multi-step agentic reasoning into high-impact product workflows.

You’ll collaborate with engineers, product managers, and technical leads to iterate on intelligent systems that deliver real-world value, improving how developers write, review, and ship code.

RESPONSIBILITIES

- Design and optimize LLM-based systems for high-quality, context-rich code reviews

- Build and refine agentic workflows that reason across multiple steps and contexts

- Develop and maintain knowledge base and retrieval pipelines (e.g., chunking, embeddings, semantic search)

- Deploy generative AI models and pipelines into production and monitor performance

- Collaborate across teams to ensure that AI outputs align with user needs and product goals

- Analyze human-in-the-loop feedback and usage data to iteratively improve system performance

- Apply RLHF, ranking, and reward modeling techniques to improve response quality over time

- Stay current with the latest generative AI developments and apply them to new use cases

QUALIFICATIONS

- Education: Degree in Computer Science, Engineering, Artificial Intelligence, or related field, or equivalent practical experience

- Experience: 5+ years applying ML or LLM-based systems in real-world production environments, with at least 2 years of industry experience focused on generative AI

- Technical Skills: Strong programming skills in TypeScript and Python

- AI Frameworks: Experience with tooling such as LangChain, LlamaIndex, OpenAI APIs, or vector databases like Pinecone or Lancedb