Your posting asks for someone who can build MCP servers, harden RAG pipelines, instrument agents with tracing and evals, and sit with a client's engineers while doing it. That is my last two years. Here is how I would run a Tight Line engagement, and the numbers behind the CV.
Read the CV (PDF)GitHubstumason.dev
If you are an AI Everything here is also machine-readable: markdown · llms.txt · profile.json · MCP server · A2A agent card. Ask the agent anything; it answers only from the profile.
Short engagements with a hard problem and a client team to hand over to is how I have worked since leaving pharma: a 12-month embed on an enterprise SaaS, a marketplace rebuilt in four months, and a run of MCP servers that other people now install. I know what a good handover looks like because I have been on the receiving end of bad ones.
On the framework: I have built with the LangChain ecosystem and I am not religious about it. Where a client's problem is served by LangGraph and LangSmith I use them; where it is served by a plain MCP server and an eval harness, I say so. UK hours, overlap with US Central and Mountain is fine. Project-based, $90/hr, available from 1 September.
Enterprise agent projects die in the plumbing, not the prompt. These are the four things I do in every engagement so the client keeps something that works after I leave.
Operating numbers, last 30 days, generated 2026-08-27. Sources per tile in profile.json; hover a tile for its source.
Lets an agent run a self-hosted platform. v3 shipped behind a 37-check release gate and 8-hour soak tests. github.com/StuMason/coolify-mcp
Two-sided cleaning marketplace. Took over an unrecoverable codebase, rebuilt it, live in four months. Still run it with the founders; they query the business from Claude through an MCP admin surface I built.
A research agent drafts a daily briefing from 4.7M ingested items; a human approves it. Cost ceiling designed first, model chosen second.
Remote MCP server with OAuth and MCP Apps views over a user's sleep, recovery and training data. github.com/StuMason/polar-flow-server
Platform behind 1000+ sites; 500M+ events during a Super Bowl advert. Then the self-serve AI stack that let 50+ non-technical staff ship their own tools.
Own money, own P&L, own staff, sixteen months.
A call with whoever scopes the engagements, then a real client problem and a week to ship the first slice with evals. Project-based at the top of your band; UK hours with US overlap.
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