The posting
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.



