Senior Python/AI Engineer — Code & Architecture Review (Written Report)

## Summary I have a working **Legal AI document platform** and need an experienced engineer to do a focused **1-hour review** and deliver a **written review document** with findings and recommendations. This is a quick, paid, one-off engagement — not ongoing development. ## About the Project A FastAPI backend that generates, reviews, modifies, and exports legal documents, with semantic search over articles and uploaded Word documents. **Tech stack:** - **Backend:** Python 3.12, FastAPI, Pydantic, async (motor) - **Data:** MongoDB (content), Pinecone (vector embeddings) - **AI:** OpenAI (embeddings + GPT for document generation/review/section explanation) - **Document processing:** python-docx, textract, reportlab/weasyprint/PyPDF2 (PDF export) - **Frontend:** Vanilla HTML/CSS/JS renderer + admin panel - **Structure:** routes / services / repositories / models layering (~10 route modules, ~12 service modules) ## Scope of Review (1 hour) Please assess and comment on: 1. **Architecture & code structure** — separation of concerns, layering, maintainability 2. **API design** — REST endpoints, validation, error handling 3. **AI/LLM integration** — prompt/embedding strategy, cost, reliability of generation/review flow 4. **Data layer** — MongoDB + Pinecone usage, consistency between the two stores 5. **Security & production-readiness** — secrets handling, auth, input validation, obvious risks 6. **Quick wins & red flags** — top issues to fix first ## Deliverable A **written review document** (Markdown, PDF, or Google Doc) containing: - Executive summary (overall health of the project) - Prioritized list of issues (Critical / High / Medium / Low) - Concrete, actionable recommendations - Any notable strengths ## Requirements - Strong **Python + FastAPI** experience - Experience with **LLM/RAG systems** (OpenAI, vector databases like Pinecone) - Familiarity with **MongoDB** and production API design - Able to start **today** and turn around within **~1 hour** of access ## Logistics - I'll provide zip at the start. - **Timeline:** ASAP — looking to have someone start within the next few hours. ## To Apply Please answer briefly: 1. Have you reviewed a FastAPI + vector-DB (RAG) project before? Share one example. 2. What's the first thing you check when auditing an LLM-backed API? 3. Your availability to start today.