Applied AI Engineer
CodeRabbit · San Francisco, CA · 8 mo ago
HybridEngineering$200k–$300k/yrFull-time
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: 3+ 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
- Prompt Engineering: Strong skills in prompt engineering
- Data Fluency: Ability to extract insight from telemetry, logs, user signals, and structured feedback
- Practical Mindset: Comfortable applying research-inspired methods to solve concrete product challenges
- Cross-Functional Collaboration: Experience working across product, engineering, and design to deliver production-grade systems
Bonus Points
- Experience optimizing RAG systems and tuning retrieval performance using custom embeddings or search strategies
- Hands-on experience with RLHF pipelines, reward modeling, or behavioral policy tuning in LLMs
- Experience integrating LLM systems into developer tooling or collaborative workflows
- Track record of contributions to open-source projects or publications in applied AI/ML
Why Join Our Engineering Culture?
- High-Ownership Engineering Culture
- Bias Toward Action
- Ship the Smallest Necessary Coherent Slice
- Validate Proportional to Risk
- Watch What Happens and Make the System Better
Compensation Range
$200K - $300K