About

Sean Traynor

AI Systems Architect. 7+ years building across the full stack. Last two years focused exclusively on agentic orchestration, multi-repo infrastructure, and production AI systems that run reliably at scale.

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Background

I build AI systems that work — not demos, not prototypes, but production systems that run daily under real operational load. My focus is on the orchestration layer: how multiple AI agents coordinate, how trust boundaries are enforced, and how knowledge compounds across sessions rather than evaporating.

My primary project is the Master OS: a custom AI operating system I designed and operate across seven business domains. It's the most distinctive evidence of my capabilities — a real system, built in public (within my own repos), that demonstrates every design pattern I know in production code.

Before focusing full-time on AI infrastructure, I spent seven years across the full stack: front-end, back-end, data pipelines, cloud infrastructure. That foundation matters — I can ship systems, not just design them.

Operating philosophy

01
Correctness over velocity. A system that breaks under load is worse than no system at all. I build invariants into hooks, not prompts — because invariants need to be enforced by the runtime, not hoped for by the model.
02
Architecture follows runtime constraints. Theoretical elegance is cheap. The right design is the one the actual system supports. I build from discovered constraints, not whiteboard diagrams.
03
Compounding knowledge is the moat. Systems that get smarter every day compound faster than static systems. Distillation pipelines, verified knowledge bases, and durable audit trails are structural advantages.
04
One command, intelligent cadence. Good systems have minimal ceremony. If it takes three commands and a manual checklist to do a thing, it won't get done consistently. I optimize for the one-command path.

Technical depth

AI / Agentic Systems

  • Claude Code orchestration and hook design
  • Multi-agent coordination and authority delegation
  • Prompt engineering and advisory/deterministic separation
  • FSM-validated state machines for agent workflows
  • Verifier/executor patterns with pre-merge gates
  • Knowledge distillation pipelines

Infrastructure

  • Multi-repo git topology and worktree management
  • CI/CD pipelines (pytest, ruff, system health checks)
  • Vercel deployments and static site optimization
  • Python scripting and automation
  • JSON schema design and validation

Product & Domain

  • Marketing automation (Meta Ads API integration)
  • EdTech product development (Sandbox Labs)
  • Music industry operations (UMANO)
  • Algorithmic trading infrastructure (isolated / read-only)
  • Technical writing and systems documentation

Front-End

  • Astro, React, Next.js
  • TypeScript / JavaScript
  • CSS architecture and design systems
  • Performance-first static site development

What I'm looking for

I'm targeting senior AI roles at frontier-AI companies — AI Engineering, AI Operations, and Solutions Architecture positions where systems thinking and production credibility matter more than résumé pattern-matching.

Companies I'm most interested in include Anthropic, Weights & Biases, Scale AI, Harvey AI, and Cognition AI — places where the work is deep, the bar is high, and the domain is advancing fast enough that building your own operating system is considered a reasonable weekend project.

Open to remote, hybrid, or NYC-based roles. Available to start within 2–4 weeks.

sptraynor2001@gmail.com LinkedIn GitHub