Senior Applied AI Engineer

CodeRabbit; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

CodeRabbit in San Francisco is seeking an Applied Gen AI Engineer to design, build, and deploy advanced generative AI systems powering our code review and developer productivity tools.

You’ll implement state-of-the-art techniques like RAG, RLHF, and multi-step agentic reasoning, collaborate across product and engineering, and drive production-ready workflows that help developers write, review, and ship code faster and more reliably.

Qualifications

• Education: Degree in Computer Science, Engineering, AI, or related field, or equivalent practical experience.
• Experience: 5+ years applying ML/LLM-based systems in production, with 2+ years in generative AI.
• Technical: Strong programming skills in TypeScript and Python.
• AI Frameworks: Experience with LangChain, LlamaIndex, OpenAI APIs, or vector databases.
• Prompt Engineering: Strong skills in crafting effective prompts.
• Data Fluency: Ability to extract insights from telemetry, logs, and user signals.
• Mindset: Comfortable applying research-inspired methods to product challenges.
• Collaboration: Proven ability to work across product, engineering, and design.

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 (chunking, embeddings, semantic search).
• Deploy generative AI models and pipelines into production and monitor performance.
• Collaborate across teams to ensure 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.

Skills

TypeScript

Python

Prompt Engineering

Cross-Functional Collaboration

Data Fluency

Practical Mindset

Education

Bachelor's degree in Computer Science or related field

Tools

LangChain

LlamaIndex

OpenAI APIs

Pinecone

Lancedb

Job description

About CodeRabbit

CodeRabbit is an innovative research and development company focused on building extraordinarily productive human-machine collaboration systems. Our primary goal is to create the next generation of Gen AI-driven code reviewers: a symbiotic partnership between humans and advanced algorithms that significantly outperforms individual engineers. We combine language models with human ingenuity to push the boundaries of software development efficiency and quality.

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

• 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?

• CodeRabbit is building the next generation of AI-native developer tooling — starting with code review. We combine large language models with deep software engineering context to help teams ship faster, catch more bugs, and make better architectural decisions at scale.

• We are a high-ownership engineering culture. That means no passive execution, no waiting for perfect tickets, and no narrowly defined task boundaries. Engineers here find problems before they're assigned, use AI as a core part of how they build, ship with judgment, and own outcomes from proposal to production.

• Our operating philosophy: bias toward action, ship the smallest necessary coherent slice, validate proportional to risk, watch what happens, and make the system better. AI drafts; humans decide. Speed matters, but so does understanding what you ship.

• This opportunity will be energizing for people who want real ownership, pace, and high standards. It’s uncomfortable for people who prefer slow consensus or heavily managed workflows.

• If you want to build tools that are changing how software gets written, and be held to the standard that the best engineers thrive under; we'd love to talk.

Our Values

• Collaborative Humans — Prioritizing collective intelligence

• Fearless Innovators — Turning obstacles into growth opportunities

• Persistent, Passionate Developers — Thriving on complex, long-term challenges

• Impact-Driven Creators — Crafting intuitive tools for developers

• Rapid Learners and Un-learners — Adapting quickly in our fast-paced technological world