Senior Full-Stack Engineer - LLM-Powered Code Review PoC

NexaFlow is building a next-generation code review tool powered by large language models. We are seeking a Senior Full-Stack Engineer to lead the development of a proof-of-concept prototype that integrates LLM-based analysis into existing CI/CD workflows.

Responsibilities

• Design and implement a full-stack application that integrates LLM APIs (OpenAI/Anthropic) for automated code review.
• Build webhook-based integrations with GitHub/GitLab to automatically analyze pull requests.
• Develop a hybrid analysis pipeline combining LLM reasoning with static analysis for bug detection, security vulnerability identification, and code quality enforcement.
• Create a configurable rule engine allowing per-repository custom review policies.
• Build a dashboard displaying review statistics, trends, and actionable insights.
• Containerize the entire solution with Docker for easy self-hosted deployment.
• Own the full lifecycle from architecture design through deployment and documentation.

Requirements

• 5+ years of professional full-stack development experience.
• Strong experience integrating LLM APIs (OpenAI GPT-4, Anthropic Claude) into production systems.
• Hands-on experience with CI/CD pipeline integration (GitHub Actions, GitLab CI).
• Prior work building code review tools, linters, or static analysis systems.
• Proficiency in Python (FastAPI) or Node.js for backend; React or Vue for frontend.
• Experience with Docker containerization and self-hosted deployment.
• Ability to work independently across the full stack from architecture to deployment.
• Strong communication skills for async collaboration.

Nice to Have

• Experience with RAG (Retrieval-Augmented Generation) architectures.
• Familiarity with CodeQL, Semgrep, or similar static analysis tools.
• Previous startup or PoC-stage project experience.
• Contributions to open-source developer tools. Additional Information:
• This is a contract/consulting engagement, not a full-time employee role.
• We value flexibility and outcome-driven collaboration.
• Remote-friendly with a preference for candidates in the San Francisco Bay Area.