14+ years building, securing, and scaling enterprise infrastructure at Wells Fargo, Tile Shop, and MidHudson Regional Hospital. Now I break AI agents before attackers do.
I spent 14 years running enterprise IT for some of the most regulated environments in the country — financial services, healthcare, retail, and higher education. The same security disciplines I used there apply directly to AI agents today.
At Wells Fargo, I led a 40-person engineering organization, governed an $80M+ technology portfolio, and directed a multi-year SD-WAN transformation across 5,000+ locations. I integrated Splunk, AppDynamics, and SevOne into operations — driving a 40% reduction in mean time to resolution. I negotiated $2M+ in carrier savings and established roadmaps for Zero Trust, hybrid cloud, and network modernization.
At The Tile Shop, I held full responsibility for enterprise infrastructure across 370+ retail locations. I led a Juniper-to-Meraki SD-WAN migration that cut WAN costs by 20%, redesigned store connectivity with LTE failover, and delivered SOX-compliant security controls.
At MidHudson Regional Hospital, I ran network engineering for 24x7 clinical operations — EMR, PACS, life-safety systems — under HIPAA. I cut patient-impacting network events from over two hours to under 30 minutes and achieved 99.99% availability for critical hospital systems.
Now I apply that same discipline to AI security. Prompt injection, tool misuse, data leakage — these are the same attack surface problems I've been solving for 14 years, just with a new protocol layer on top.
Enterprise IT security and AI security share the same fundamentals: identity, access control, data boundaries, and monitoring. The difference is speed — AI agents can be exploited in milliseconds through prompt injection, and the attack surface changes every time you update a system prompt or add a tool.
I bring 14 years of enterprise-grade security discipline — Zero Trust architecture, network segmentation, incident response, vendor risk management — to a field where most practitioners have never run a production environment at scale. That's the GaleOps difference.
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