AI Systems Architect · Context Architecture · Multi-Agent Orchestration · Evaluation Pipeline Design
I design and deploy autonomous AI systems at enterprise scale in regulated industries. I am not an AI strategist who advises from the sidelines — I build production systems and I operate the infrastructure I design.
My independent R&D produced a live multi-agent operating system: 20+ specialized agents executing across strategy, governance, finance, and build operations with zero human operator touchpoints. This runs daily as primary business infrastructure. Not a demo. Not a prototype.
My enterprise track includes designing AI governance architecture for Fortune 500 programs — ADR-gated deployment frameworks, curated knowledge systems, evaluation protocols, and permission enforcement models for 500-developer platforms in regulated industries. Architecture for systems that survive compliance review, not proof-of-concept demos.
The differentiator: I build production autonomous AI systems independently AND I design enterprise governance architecture at Fortune 500 scale. One proves I can ship. The other proves I can ship inside organizations where security, compliance, and governance are non-negotiable.
comprehension-audit — Open-source AI project comprehension diagnostic. Dual-run LLM judge, 8-dimension weighted scoring, L1–L5 maturity bands, prompt injection sanitization, graceful degradation. Each module ships with an EXPLANATION.md — architectural decision records explaining the why behind every design choice.
Context Architecture — The layer that determines whether AI systems produce real ROI or expensive demos. Specification quality, knowledge graph design, retrieval strategy.
Multi-Agent Orchestration — Agent taxonomy, task decomposition, failure-mode supervision, automated quality gates. Production systems, not proof-of-concepts.
Evaluation Pipelines — Drift detection, hallucination mitigation, audit-ready logging. The layer that separates AI pilots from AI systems that survive regulatory review.
Dark Factory Methodology — Fully autonomous operational pipelines. Zero operator touchpoints between specification and delivery. L4–L5 maturity.
Azure OpenAI · Semantic Kernel · Python · C#/.NET · TypeScript · LangFlow · LangChain · Claude AI · RAG Pipelines · FastAPI · React · Astro · Node.js · GitHub Actions · Netlify
AZ-305 Solutions Architect Expert · AZ-204 Developing Solutions for Microsoft Azure · AZ-104 Azure Administrator · AZ-900 · AI-900 · DP-900 · SC-900