Senior Applied AI Engineer
Hybrid (San Francisco)$200k - $300kFull-timePosted 11mo ago
About the role
Role focused on designing, building, and deploying advanced generative AI systems to power CodeRabbit’s code review and developer productivity tools, incorporating techniques like RAG, RLHF, and multi-step agentic reasoning.
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
- Degree in Computer Science, Engineering, Artificial Intelligence, or related field, or equivalent practical 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
- Strong programming skills in TypeScript and Python
- Experience with LangChain, LlamaIndex, OpenAI APIs, or vector databases like Pinecone or Lancedb
- Strong skills in prompt engineering
- Ability to extract insight from telemetry, logs, user signals, and structured feedback
- Comfortable applying research-inspired methods to solve concrete product challenges
- Experience working across product, engineering, and design to deliver production-grade systems
Skills
Required:LLM-based system designAgentic reasoningKnowledge base & retrievalProduction AI deploymentPrompt engineering
Last updated Aug 19, 2026. Interested? Apply on the company site.
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