I help enterprises adopt AI without inheriting a new category of risk.

Two decades on the security side of hard problems

I've spent over twenty years in IT — beginning in software engineering and evolving through enterprise identity, cloud platform security, and Zero Trust into the security and governance of enterprise AI. Today, at Microsoft, I own cybersecurity strategy and multi-year roadmaps for some of the world's largest financial institutions, partnering with CISOs and C-suite leaders to align security to risk appetite, regulatory obligations, and business growth.

Securing enterprise AI at Microsoft

For the past few years my focus has been AI and agentic security: helping financial customers operationalize AI security for generative and agentic AI adoption. That means designing controls for LLM and agentic systems — prompt injection, MCP server security, and the OWASP Top 10 for LLMs — and defining how AI agent identities are inventoried, scoped to least privilege, and continuously monitored. I pair governance guardrails and risk assessments with the architecture and detection engineering that make them real.

Cloud security, identity, and red teaming

My foundation is deep cloud security across Azure, AWS, and GCP — security guardrails, CSPM, and reference architectures for regulated workloads — and more than a decade of identity and access work spanning IGA, PAM/PIM, workforce, B2B, and CIAM. I bring a red-team and threat-modeling mindset to everything: hypothesis-driven hunts, adversary-technique-mapped detection content, and architecture reviews that find the gaps before an attacker does.

Strategy grounded in business

An Executive MBA from the University of Maryland's Robert H. Smith School of Business sharpened how I connect security to business outcomes — risk, operating models, and the economics of adoption. I write and speak regularly on securing agentic systems, governing AI at scale, and building identity-first foundations for enterprise AI.