Chris M.

𝗠𝗼𝘀𝘁 𝗔𝗜 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗱𝗶𝗲 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗣𝗢𝗖 𝗮𝗻𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻. 𝗜 𝘀𝗵𝗶𝗽 𝘁𝗵𝗲 𝗼𝗻𝗲𝘀 𝘁𝗵𝗮𝘁 𝗱𝗼𝗻'𝘁. Companies say they want one person who can set AI strategy, be AI-native enough to build it, lead the engineers who scale it, and deliver product. 𝗧𝗵𝗮𝘁 𝗽𝗲𝗿𝘀𝗼𝗻 𝗶𝘀 𝗺𝗲.

I'm a 𝗙𝗿𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗧𝗢 / 𝗖𝗵𝗶𝗲𝗳 𝗔𝗜 𝗢𝗳𝗳𝗶𝗰𝗲𝗿 𝗮𝗻𝗱 𝗵𝗮𝗻𝗱𝘀-𝗼𝗻 𝗯𝘂𝗶𝗹𝗱𝗲𝗿. I lead AI product strategy and architecture, then get into the code: AI agents, RAG pipelines, and automation, plus the observability, guardrails, and governance that keep them alive in production. I separate deterministic infrastructure from probabilistic reasoning so failures are traceable and costs are bounded.

𝗜 𝗯𝘂𝗶𝗹𝗱 𝘄𝗶𝘁𝗵 Cursor, Claude (incl. Claude Code and MCP), OpenAI, Python, and a modern full stack: React / Next.js / Node / TypeScript, Supabase / PostgreSQL, on AWS. I orchestrate workflows with n8n, Make, and Zapier, and ship production voice and agent systems (Retell, Vapi, Twilio) for regulated environments.

𝗔𝗻𝗱 𝗜 𝗹𝗲𝗮𝗱. I set the roadmap, make the build-vs-buy and model calls, stand up evaluation and governance, and bring junior engineers up to deliver. You get a strategist who has actually built the thing, not a deck, and not a coder who's never owned production.

𝗥𝗲𝗰𝗲𝗻𝘁 𝗔𝗜 𝗯𝘂𝗶𝗹𝗱𝘀:

• 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗥𝗔𝗚 𝘄𝗶𝘁𝗵 𝗮𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗲-𝗯𝗮𝘀𝗲𝗱 𝗮𝗰𝗰𝗲𝘀𝘀 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 (𝗔𝗕𝗔𝗖): granular, per-user control over what data a chatbot can surface, so RAG is safe in regulated environments.
• 𝗦𝗲𝗿𝘃𝗲𝗿𝗹𝗲𝘀𝘀 𝗥𝗔𝗚 𝗼𝗻 𝗔𝗪𝗦 that costs $0 at rest and scales cost with revenue, ingesting email, documents, and file storage.
• 𝗔𝗜 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗮𝗻𝗱 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗽𝗼𝗿𝘁𝗮𝗹 𝗳𝗼𝗿 𝗮 𝗹𝗮𝘄 𝗳𝗶𝗿𝗺: automated intake, classification, and review across long, multi-source documents.
• 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝘁𝗵𝗮𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗮 𝗵𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗿𝗲𝗳𝗲𝗿𝗿𝗮𝗹 𝘀𝘆𝘀𝘁𝗲𝗺: POC to production in 8 weeks, 60% less manual review.
• 𝗪𝗵𝗶𝘀𝗽𝗲𝗿 𝗺𝗲𝗲𝘁𝗶𝗻𝗴-𝘁𝗼-𝘁𝗿𝗮𝗻𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 that replaced a vendor and saved $3K/month.
• 𝗥𝗲𝗮𝗹-𝘁𝗶𝗺𝗲, 𝗥𝗲𝗱𝗶𝘀-𝗯𝗮𝘀𝗲𝗱 𝗶𝗻-𝗰𝗮𝗹𝗹 𝘀𝗮𝗹𝗲𝘀 𝗰𝗼𝗮𝗰𝗵𝗶𝗻𝗴 𝗮𝗽𝗽 for live conversations.

𝗥𝗲𝗰𝗲𝗻𝘁 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝗿𝗼𝗹𝗲𝘀:

• 𝗔𝗜 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗿, 𝗦𝘁𝗿𝗶𝗱𝗲 (𝗹𝗮𝗿𝗴𝗲 𝗨𝗦 𝗼𝗻𝗹𝗶𝗻𝗲 𝗲𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻 𝗽𝗿𝗼𝘃𝗶𝗱𝗲𝗿): own the AI lifecycle and governance for the tooling that QAs course content at scale, evals, guardrails, and human-in-the-loop QA.