---
title: 'Senior Applied AI Engineer at CodeRabbit'
canonical: 'https://feeny.ai/job/senior-applied-ai-engineer-coderabbit-san-francisco-xc7bq9815n93'
type: 'job'
last_seen: '2026-09-09'
---

# Senior Applied AI Engineer at CodeRabbit

- **Company:** [CodeRabbit](https://feeny.ai/companies/coderabbit)
- **Location:** San Francisco, CA
- **Compensation:** $200k–$275k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2025-09-18
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/coderabbit/8f17b66f-ea44-4e83-85f6-ef9427d61a01/application

**Skills:** TypeScript, Python, LLM, LangChain, LlamaIndex, OpenAI APIs, Vector databases, Pinecone, Lancedb, Prompt Engineering, RAG, RLHF, Retrieval Performance Tuning, RAG optimization, Custom embeddings, LLM integration, Developer tooling

> Design, build, and deploy advanced generative AI systems for code review and developer productivity. Integrate RAG, RLHF, and agentic reasoning techniques into production workflows to enhance software development efficiency.

## Job description

## ABOUT CODERABBIT

CodeRabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million code reviews each week. We build the symbiotic partnership between developers and AI that makes shipping fast software safe again, reviewing every pull request, IDE change, and CLI commit so teams can move quickly without breaking things.

We are a fast-moving, well-funded company, fresh off a $143M Series C at a $1.5B valuation — building Agentic Change Management, the control layer for software changes created by humans and agents. As AI writes more of the world's code, the bottleneck moves from implementation to judgment and helping human judgment scale is exactly the problem we exist to solve.

## 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

## About CodeRabbit

## Company Overview
- **One-liner**: CodeRabbit is an AI‑powered platform that automates the first pass of code reviews, providing context‑aware, human‑like feedback to help development teams ship faster and catch more bugs.
- **Entity Type**: Private (Series B; total funding $79.61M; last round $60M in October 2025)
- **Headquarters**: San Francisco, United States (also reported as Walnut Creek, California – conflicting reports)
- **Founded**: 2023
- **Founders**: Harjot Gill (CEO) is the primary founder; other co‑founders are not publicly disclosed.

## Core Business
- **Primary industries**: Software Development, AI‑powered Developer Tools
- **Target customers**: B2B, serving Engineering teams across SMB and Enterprise (15,000+ customers including The Economist, Life360, ConsumerAffairs, Hasura)
- **Mission / purpose**: “Revolutionize how code reviews are done” – enabling teams to move fast while maintaining code quality.

## Products & Services
- **CodeRabbit AI Review (SaaS / API)**: An AI‑powered code review agent that integrates with GitHub, GitLab, and other platforms. It provides line‑by‑line feedback, code suggestions, architectural diagrams, unit‑test generation, docstring creation, and a “Chat with CodeRabbit” feature. Supports custom guidelines, path/AST‑based instructions, and learns from developer feedback (“Learnings”).

## Market Standing
- **Valuation / Market Cap**: Not publicly disclosed (private company)
- **Key Metric**: **Total Funding** – $79.61 million raised (Series B led by Scale Venture Partners at $60M, October 2025)
- **Notable Investors / Partners**: Scale Venture Partners (lead, Series B), CRV (lead, Series A), Engineering Capital, Harmony Partners, NVentures (NVIDIA), and 8+ other investors.
- **Growth Signals**:
  - Headcount: 154 employees, **+363.6% year‑over‑year**.
  - Customer base grew to 15,000+.
  - SOC 2 Type II certified; GDPR compliant.
  - Acquired FluxNinja in 2024.
  - Claimed as “Most installed AI App” (quote attributed to Jensen Huang, NVIDIA CEO) on homepage.
  - Active job postings: **39** (yearly increase of +550%).

## Competitive Advantages
- **Continuous learning**: AI agent improves over time by incorporating developer feedback in natural language.
- **Deep context**: Uses Codegraph, MCP servers, linked issues (Jira, Linear), and web queries to understand dependencies across files.
- **Noise reduction**: 40+ linters and security scanners are integrated while false positives are filtered out.
- **Customizability**: Entire review workflow can be configured via a YAML file, including custom checks and coding guidelines.
- **Security‑first**: End‑to‑end encryption, zero data retention post‑review, independent SOC 2 Type II audits.

## Strategic Focus
- **Expand pre‑merge checks** and finishing touches (e.g., custom checks in natural language).
- **Deepen IDE & CLI integration** to review code even before PRs are created.
- **Enterprise growth**: Hiring senior sales roles (Enterprise AE, Sales Manager) and expanding into EMEA and APAC markets (e.g., South Korea).
- **Continuous improvement** of AI agent through user feedback and expanded external context sources.

## Why Work Here
- **Culture**: Described as fast‑paced, innovation‑driven, collaborative, and impact‑oriented. Values: fearless & innovative, persistent & passionate, impact‑driven.
- **Work model**: Hybrid/office‑first (San Francisco office with daily catered lunch); remote roles may be available for some positions.
- **Compensation & perks** (from careers page):
  - Unlimited PTO
  - Premium medical, dental, vision coverage
  - 401(k) for U.S. hires
  - Stock options (high growth potential)
  - Monthly commuter stipend
  - Learning & development stipend
- **Employee sentiment**: 3.8/5 on LinkedIn (11 reviews), with Compensation at 4.2, Career growth at 4.1, and Culture at 3.8.
- **Engineering culture**: Technical team makes up 28% of headcount; employees use and improve the AI tool themselves; strong emphasis on shipping fast without breaking things.

## Sources
1. [coderabbit.ai/careers](https://coderabbit.ai/careers)
2. [coderabbit.ai](https://coderabbit.ai/)
3. [cbinsights.com/company/coderabbit](https://www.cbinsights.com/company/coderabbit)
4. [linkedin.com/company/coderabbitai](https://www.linkedin.com/company/coderabbitai)
5. [jobs.ashbyhq.com/coderabbit](https://jobs.ashbyhq.com/coderabbit)

## Other roles at CodeRabbit

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- [Product Manager - All Levels](https://feeny.ai/job/product-manager-all-levels-coderabbit-san-francisco-ayja997n2dqp) — San Francisco, CA
- [Product Designer](https://feeny.ai/job/product-designer-coderabbit-san-francisco-zbb23fes7k1g) — San Francisco, CA
- [Visual Designer](https://feeny.ai/job/visual-designer-coderabbit-san-francisco-754xdckkq0st) — San Francisco, CA
- [Design Engineer](https://feeny.ai/job/design-engineer-coderabbit-san-francisco-z436m5fapszn) — San Francisco, CA
- [Office Coordinator - Boston](https://feeny.ai/job/office-coordinator-boston-coderabbit-boston-12wxq0pm9k31) — Boston, MA
- [Content & Enablement Specialist](https://feeny.ai/job/content-enablement-specialist-coderabbit-boston-h30ktf0cn9hj) — Boston, MA
- [Product Manager: Security](https://feeny.ai/job/product-manager-security-coderabbit-bengaluru-6e07wzx2h36n) — Bengaluru, India
- [Enterprise Customer Success Manager, Americas](https://feeny.ai/job/enterprise-customer-success-manager-americas-coderabbit-san-francisco-pmd9047jxbmr) — San Francisco, CA
- [Commercial Field Engineer – Post-sales](https://feeny.ai/job/commercial-field-engineer-post-sales-coderabbit-london-96barc7gjnec) — London, United Kingdom