The intersection of AI and security has defined my career.

I’m an AI Security Engineer at MasterControl, where I own the company’s AI security program for 600 employees end to end: leading governed model access through LiteLLM and the staged rollout of Onyx guardrails, driving AI governance through our Acceptable Use Policy and staged technical enforcement, and designing detection coverage for prompt injection, data leakage, and shadow AI. I also developed the required AI security training for our engineering teams.

Before stepping into AI security, I worked in cloud security and vulnerability management in a FedRAMP environment — Tenable, Wiz, and AWS for NIST 800-53 compliance, keeping scanning coverage audit-ready, and a Security Champions Program that put a named owner for security findings on each team. Earlier, in Security Operations, I deployed NIDS and honeypots, validated detection rules through adversary simulation, and built real-time dashboards for executive visibility.

The through-line is that I would rather build a control point than write a rule. Most of what I do is finding the one place a class of risk can actually be enforced — a gateway, an admission controller, a merge gate — and then making that path the one people would choose anyway. You can read those in detail under selected work.