You will get Production Ready AI SaaS MVP | Next.js, FastAPI, OpenAI & Stripe
Rising Talent
Rising Talent
Project details
Your AI SaaS idea deserves better than a demo that falls apart in production. I will design and build your AI SaaS product end to end: the platform, the product, and the AI core, engineered by one senior engineer who has done it at enterprise scale for 8+ years.
What you get:
• Multi-tenant SaaS platform: authentication, roles, Stripe billing, dashboards
• The AI core designed in, not bolted on: OpenAI, Claude, or Gemini with structured outputs and function calling.
• Production hardening: evaluation suites, tracing, cost monitoring, security (RBAC, secrets, audit logs)
• Modern stack: Next.js, React, TypeScript, Python FastAPI, PostgreSQL, Redis, AWS or GCP
• Documented handoff: you own the code, no vendor lock in, your team maintains it
Process: scoping call, written architecture proposal, working prototype in weeks, production hardening, documented handoff.
I have shipped production AI SaaS platforms for support, content, and sales automation.
What you get:
• Multi-tenant SaaS platform: authentication, roles, Stripe billing, dashboards
• The AI core designed in, not bolted on: OpenAI, Claude, or Gemini with structured outputs and function calling.
• Production hardening: evaluation suites, tracing, cost monitoring, security (RBAC, secrets, audit logs)
• Modern stack: Next.js, React, TypeScript, Python FastAPI, PostgreSQL, Redis, AWS or GCP
• Documented handoff: you own the code, no vendor lock in, your team maintains it
Process: scoping call, written architecture proposal, working prototype in weeks, production hardening, documented handoff.
I have shipped production AI SaaS platforms for support, content, and sales automation.
What's included
| Service Tiers |
Starter
$1,500
|
Standard
$3,900
|
Advanced
$7,900
|
|---|---|---|---|
| Delivery Time | 15 days | 35 days | 50 days |
Number of Revisions | 1 | 2 | 3 |
Design Customization | - | ||
Content Upload | - | ||
Responsive Design | |||
Source Code | - | - |
About Michael
Full-Stack AI Engineer | AI SaaS, LLM, Python, LangChain, MCP Servers
Vancouver, United States - 9:33 am local time
I've spent the last 8+ years as a Senior Full-Stack AI Engineer in enterprise SaaS, on products where “it mostly works” was never an acceptable answer. Now I bring that same discipline to your AI SaaS products: the platform, the product, and the AI core, built end to end by one person who's done it at scale.
𝐖𝐇𝐀𝐓 𝐈 𝐁𝐔𝐈𝐋𝐃
• AI SaaS products, end to end - multi-tenant platforms with authentication, billing, dashboards, and the AI core designed in, not bolted on
• AI agents and multi-agent systems - LangGraph-based agents with the parts most builds skip: evaluation suites, monitoring, cost controls, and guardrails
• LLM applications and AI integration - OpenAI, Claude, and Gemini embedded in your product with structured outputs, function calling, and production-grade reliability
• RAG and knowledge systems - retrieval pipelines over your data with hybrid search, reranking, and measurable answer quality
• MCP servers and integrations - connecting AI to your CRM, databases, and internal tools through the Model Context Protocol
• Production operations - MLOps and LLMOps (evaluation pipelines, tracing, model and cost monitoring), DevOps (containerized deployments, CI/CD), and SecOps (authentication and RBAC, secrets management, audit logging)
𝐇𝐎𝐖 𝐘𝐎𝐔𝐑 𝐏𝐑𝐎𝐃𝐔𝐂𝐓 𝐆𝐄𝐓𝐒 𝐁𝐔𝐈𝐋𝐓
Scoping call - written architecture proposal - working prototype in weeks, not months - production hardening (evals, observability, security, cost) - documented handoff. You own the code. No vendor lock-in, no black boxes, and your team can maintain what I leave behind.
𝐓𝐄𝐂𝐇 𝐒𝐓𝐀𝐂𝐊𝐒
• Backend: Python, FastAPI, Node.js, PostgreSQL, Redis, Stripe
• Frontend: Next.js, React, TypeScript, Tailwind CSS, Vue.JS
• AI / LLM: OpenAI (GPT-4o and o-series), Anthropic Claude, Gemini, LangChain, LangGraph, LangSmith, MCP
• Retrieval: Pinecone, Qdrant, Weaviate, pgvector
• DevOps & Cloud: AWS, GCP, Docker, Kubernetes, CI/CD
• MLOps / LLMOps: LangSmith tracing, evaluation pipelines, model and cost monitoring
• SecOps: authentication and RBAC, secrets management, audit logging, security-first code review
𝐈𝐍𝐃𝐔𝐒𝐓𝐑𝐈𝐄𝐒
B2B SaaS, Marketing, fintech and financial services, healthcare, legal and professional services - environments where reliability, security, and compliance are not optional.
𝐖𝐇𝐘 𝐂𝐋𝐈𝐄𝐍𝐓𝐒 𝐇𝐈𝐑𝐄 𝐌𝐄
Most engineers are strong on the AI layer or the product layer. I've spent my career on both: the same person who designs your retrieval pipeline can build the dashboard, wire the billing, and get it deployed, then keep it observable, secure, and affordable in production. That's the difference between shipping a demo and shipping a product.
Send me a short message: what your product does (or will do), what stage it's at, and what's blocking you. I'll reply with an honest read and a concrete next step.
Steps for completing your project
After purchasing the project, send requirements so Michael can start the project.
Delivery time starts when Michael receives requirements from you.
Michael works on your project following the steps below.
Revisions may occur after the delivery date.
Scoping call and written architecture proposal.
Build in weekly demo increments: platform first, AI core designed in.