Applied AI Engineer
CodeRabbit1 year ago
Base Salary
$175k - $275k/yr
Responsibilities
- Design and optimize LLM-based systems for context-rich code reviews.
- Build and refine multi-step agentic workflows.
- Develop and maintain knowledge-base and retrieval pipelines, including chunking, embeddings, and semantic search.
- Deploy generative AI models and pipelines to production and monitor performance.
- Use human-in-the-loop feedback, usage data, ranking, and reward modeling to improve system quality.
- Collaborate with engineering, product, design, and technical leads to deliver AI workflows aligned with user needs.
- Track generative AI developments and apply them to new product use cases.
Requirements
- Degree in Computer Science, Engineering, Artificial Intelligence, or a related field, or equivalent practical experience.
- At least 3 years applying ML or LLM-based systems in real-world production environments, including at least 2 years focused on generative AI.
- Strong programming skills in TypeScript and Python.
- Experience with LangChain, LlamaIndex, OpenAI APIs, or vector databases such as Pinecone or Lancedb.
- Strong prompt engineering skills and ability to analyze telemetry, logs, user signals, and structured feedback.
- Experience applying research-inspired methods to concrete product challenges and collaborating across product, engineering, and design.
- Preferred experience optimizing RAG retrieval, using custom embeddings or search strategies, working with RLHF and reward modeling, integrating LLMs into developer tools, or contributing to open-source projects or publications.
Benefits
- Competitive salary, equity, and benefits package.
- Hybrid work culture with weekly in-person collaboration and flexibility for remote heads-down work.
- Mentorship, responsibility, and professional development opportunities.
- End-to-end project ownership from proposal through production.
Tech Stack
Categories
About CodeRabbit
CodeRabbit builds an AI-powered code review platform for software development teams, integrating with Git hosts, IDEs, and CI to review pull requests and commits, surface issues, and suggest fixes. Founded in 2023 and based in San Francisco, the privately held company is SOC 2 Type 2 and GDPR compliant and lists customers such as The Economist and Life360.