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I join when operations, commerce, or science have outgrown their systems — and I ship both the product people will use and the AI platform underneath it.
This site is the SYSTEMS catalog: Kitchen Kontrol, NeuroNote, Tokyo Eye, Canon Forge, the Azure MLOps factory, and the AI/ML Engineer Academy. Two resume cuts share that spine — product leader, and GenAI/ML architect. LinkedIn currently wears the architect headline. The work here is the proof, not a studio reel.
GenAI/ML architect and product leader with 25 years delivering enterprise software, data, and transformation programs. Builds governed AI from infrastructure through model and agent runtime — Azure ML, Databricks, Foundry, MLflow, Terraform — and ships the product that actually gets adopted on the floor. I join at the inflection: ops, commerce, or science that has outgrown its systems.
Azure ML, Databricks, Foundry, RAG, agents, MCP tool boundaries
Local-to-cloud lifecycle, registry, promotion gates, drift, rollback
Terraform, GitHub Actions, Entra/OIDC, least-privilege split
Immutable metrics, digest-bound apply, unproven work stays off the ledger
D2C, subscription, frontline ops — AI inside the workflow, not beside it
Fortune 500 modernization, CRM, commerce, data, integration
California State University, Dominguez Hills
University of California, Irvine