The background behind the work.

AI as orchestration logic — not inference handed off and hoped for.

Built a talent-matching system where the hard engineering isn't the model — it's the confidence calibration that determines when a match surfaces versus stays in the queue. Designed a contract-monitoring system that watches partner API specs for schema drift, routes breaking changes through human review, and auto-heals downstream records once the upstream fix lands. Fortune 500 production systems, not demos.

Making a dozen clinical systems coherent enough to act on.

Director of Enterprise Data Architecture at Community Health Network — a multi-hospital system where patient data lived across platforms that were never designed to talk to each other. Built the integration layer, master data management, and unified data warehouse that made the system coherent. The design constraint in healthcare data isn't throughput — being wrong about a patient record is a patient safety problem. That changes every architecture decision downstream.

Full-stack delivery ownership, across every vertical that handles data badly.

Multi-year engagements in healthcare, manufacturing, and finance — IoT pipelines for factory floors, financial data warehouses under SLA pressure, integration platforms mid-migration. Onshore and offshore teams. The pattern recognition from running those engagements — knowing where the failure modes are before they surface — is what an engagement with Aethera is actually buying.