· Implement and operate AI security posture management (AISPM/DSPM) across model and inference infrastructure; identify misconfigurations, drift, and risk in AI workloads and drive remediation.
· Design, build, and run model validation and evaluation harnesses to test AI models and pipelines for robustness, data leakage, and unexpected behavior before and after deployment.
· Build and maintain inference-layer guardrails and controls (input/output filtering, rate and access controls) for GenAI and agentic applications.
· Define and enforce PHI/PII and data-protection controls, and identity/access controls (least-privilege, agent-to-agent authentication) for AI systems.
· Partner with Cloud Security to establish and validate guardrails in AWS and Azure for AI workloads.
· Develop scripts, automation, and tooling (primarily Python) to integrate AI security controls and automated testing into CI/CD pipelines and engineering workflows.
· Document secure architecture patterns, anti-patterns, and reference materials for model deployment and inference, and provide remediation guidance to engineering teams.
· Research, test, and pilot AI security tools and utilities aligned to the NIST AI RMF and related standards.
· Transition matured AI security monitoring to security operations teams.