AI security infrastructure, at production scale
I build and run the infrastructure behind AI runtime security — the layer that screens traffic between applications and large language models in real time. My work spans model serving and inference, CI/CD and automated testing, multi-region Kubernetes deployments, and the observability and on-call practices that keep production ML services fast and reliable. The goal: security checks thorough enough to trust and fast enough that nobody notices them.