Brett C.

Senior full stack engineer. I design, build, and keep production systems running: React and TypeScript on the front, Node and Python on the back, AWS underneath. When the product needs an AI layer, I ship that too, and I keep it in production. I have spent 30 years across the whole stack. I am the person who takes a product from the first working version through to something a team can run: APIs, data, auth, deploys, and the parts that break at 2am. Clients hire me when they need one senior engineer who can own the build, not a handoff between five roles. What I build - Product front ends in React and TypeScript, including complex editors and data-heavy UIs - APIs and services in Node.js and Python - AWS backends: EKS, Lambda, RDS, S3, CloudFront, Fargate - Data paths that have to stay correct under load, including video and large-file pipelines - The AI layer inside an existing product: RAG, tool-using agents, and multi-step workflows wired to real data and real permissions AI is part of the system, not a demo. Recent production work is an AI graphics and video platform: multi-agent workflows, retrieval over the product's own data, and processing pipelines on AWS EKS and Lambda. Before that, the same pattern on SaaS and internal tools: design the system, build it, and leave it running. How I work I start from the outcome and the constraints, not from a framework. I will tell you if the AI feature should be a normal CRUD screen. I write the code, review it, and stay through release. Fixed scope or retainer both work. I am used to async remote work and clear written updates. Stack I use on real projects React, TypeScript, Node.js, Python, PostgreSQL, AWS (EKS, Lambda, RDS, S3, CloudFront), Docker, CI/CD. AI work sits on that same stack: retrieval, agents, and tool use, with LangChain and Mastra where they earn their place. If you need a senior full stack engineer who can also own the AI pieces without turning the product into a prototype, send the brief.