i want ot create a website\app about Tea.

I’m looking for an experienced backend-focused AI engineer with strong expertise in Node.js, LangGraph, and RAG pipelines to improve and scale our existing production system. The system processes incoming emails, classifies intent, extracts information from PDF attachments, and powers a high-precision question-answering interface. The primary objective is to optimize the existing architecture, improve retrieval accuracy, reduce hallucinations, and achieve a target of 95% end-to-end pipeline accuracy through systematic testing and evaluation. The developer should be experienced in: - Node.js and LangGraph - RAG architecture and advanced retrieval techniques - PDF parsing, document processing, and information extraction - Email classification and workflow automation - LLM evaluation, prompt engineering, and accuracy optimization - Automated testing, regression testing, and debugging - Production performance optimization and scalable backend design I will provide the existing codebase, implementation requirements, and testing guidelines. The selected developer must analyze the current implementation, identify bottlenecks, implement improvements, and validate the results against a defined test dataset. **Expected deliverables:** - Improved retrieval and answer accuracy - A measurable evaluation framework with baseline and final results - Comprehensive testing across normal, edge, and failure scenarios - Regression tests to prevent existing functionality from breaking - Clear documentation of changes, findings, and remaining limitations I’m looking for someone who can work with an existing production codebase, take ownership of the technical improvements, communicate progress clearly, and demonstrate measurable results rather than simply making code changes. Please share relevant experience with production RAG systems, LangGraph, and LLM evaluation, along with examples of similar projects you have delivered.