Senior Full Stack AI Engineer for SaaS MVP Architecture

I’m looking for a senior Full Stack / AI Engineer to review an early-stage SaaS MVP and help define the right technical direction before we continue development. This is a short-term 1–2 day engagement. The goal is to evaluate the current product idea, feature scope, system architecture, AI feature requirements, database design, API structure, and deployment approach, then provide a clear technical roadmap for building a production-ready version one. I do not need a basic chatbot or simple AI API wrapper. I’m looking for someone who understands how to design AI-powered SaaS products with strong backend architecture, clean frontend structure, scalable data models, secure authentication, role-based access, API integrations, and reliable production behavior. Scope of work: Review the current SaaS/MVP concept, product requirements, or existing codebase Identify architecture gaps, technical debt, scaling risks, and unnecessary feature complexity Recommend the best version-one product scope and technical implementation plan Review frontend architecture using React, Next.js, TypeScript, and modern UI patterns Review backend architecture using Python, FastAPI, Node.js, REST APIs, or serverless functions Review database structure, schema design, PostgreSQL/Supabase setup, indexes, and data relationships Evaluate AI feature architecture, including LLM integration, prompt structure, RAG, vector search, embeddings, and context handling Review authentication, RBAC, multi-tenant structure, API security, and user permission flows Suggest improvements for performance, error handling, logging, testing, CI/CD, and deployment Provide a concise technical roadmap with milestones, risks, and recommended next steps Optional: build or improve one small proof-of-concept feature if time allows Ideal freelancer: Strong full-stack development experience with SaaS products or MVP builds Hands-on experience with AI-powered product features, not just basic API calls Strong with React, Next.js, TypeScript, Python, FastAPI, Node.js, PostgreSQL, and Supabase Experience with RAG pipelines, embeddings, vector databases, LLM integration, and API-driven architectures Comfortable reviewing architecture, code quality, database design, security, and deployment strategy Able to think like a product-minded engineer and push back on features that should not be built yet Clear communicator who can explain technical decisions in a practical, founder-friendly way Deliverable: A practical technical roadmap that explains what to build first, what to avoid, which architecture and stack to use, what technical risks need to be solved, and how to move from the current state to a production-ready SaaS MVP. Please apply with one example of a SaaS, AI product, full-stack platform, or MVP you helped design, build, or improve.