I lead high-stakes data and AI work for healthcare, government, and Fortune 100 clients — statewide election infrastructure, petabyte-scale analytics platforms, agentic AI in regulated environments, Fortune 100 database fleets. Thirty years of shipping systems that have to work on the first day, under real load.
A fully automated AI system that calls and texts patients to check on their wellbeing, scores every conversation in real time for clinical risk, and hands off patients-in-need to live staff — operating under HIPAA and clinical-safety constraints from day one.
A production system that reads ~3 million inbound clinical documents monthly — ER records, specialist notes, labs, faxes — and uses vector embeddings to surface high-risk conditions for clinical review in near real-time.
A purpose-built change data capture engine replacing commercial CDC tooling across five heterogeneous source systems — 8 million events per day at baseline, peaks over 40 million, end-to-end latency consistently under two minutes.
Near-real-time CDC capture from PostgreSQL into Snowflake, plus high-volume file-processing infrastructure, for a company that manages hospital patient flow, capacity, and throughput — HIPAA-bound and operationally critical.
Moving 24 Oracle instances onto a 13-site multi-master MariaDB topology that had to survive county-level network outages and keep elections running. Delivered three months ahead of a $12M contract. Still at 100% uptime through hundreds of election cycles.
An orchestration abstraction layer managing the full server lifecycle across 110,000 servers, 20 data centers, and seven regions spanning public cloud, FedRAMP, and private cloud — replacing an operational estate of 60,000 hand-run scripts.
This is a sample. The full CV covers thirty years of engagements, and the complete project index lists everything I can talk about publicly — long-form write-ups are being published progressively. Get in touch if any of it is relevant to work you’re doing.