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Applied AI Engineer

Roles & Responsibilities

  • Degree in Computer Science, Engineering, Artificial Intelligence, or a related field, or equivalent practical experience.
  • 3+ years applying ML or LLM-based systems in production environments, including at least 2 years focused on generative AI.
  • Strong programming skills in TypeScript and Python; experience with AI tooling such as LangChain, LlamaIndex, OpenAI APIs, and vector databases like Pinecone or Lancedb.
  • Data fluency with telemetry, logs, user signals, and structured feedback; comfortable applying research-inspired methods and collaborating across product, engineering, and design teams.

Requirements:

  • 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 bases and retrieval pipelines (e.g., chunking, embeddings, semantic search).
  • Deploy generative AI models and pipelines into production and monitor performance.

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: 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 Us?

  • Build the Future: Help shape a new development paradigm with cutting-edge technology that has real-world impact.

  • Real Ownership: Every engineer owns projects end-to-end — from proposal to production.

  • Collaborative & Innovative Environment: Join a tight-knit team passionate about building transformative products.

  • Professional Growth: We invest in our people through mentorship, responsibility, and development opportunities.

  • Competitive Compensation: Strong salary, equity, and benefits package.

  • Hybrid Work Culture: Weekly in-person collaboration with flexibility for heads-down remote work.

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

Base pay range for this role is $200k-275k. Actual salary will be based on job-related skills, experience, and location.

Apply Now — If you're excited to push the frontier of applied AI with practical impact, we’d love to meet you.

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