Leads enterprise AI security architecture and strategy across LLM applications, RAG pipelines, agent workflows, and cloud-native platforms. Establishes security standards, governance requirements, guardrails, threat models, and secure development patterns. Drives remediation of AI-specific risks including prompt injection, jailbreaks, data exposure, unsafe tool usage, and excessive permissions. Partners with senior engineering, product, architecture, and security leaders, leads investigations, supports automated security testing, represents AI security in governance forums, and mentors security engineers.

Design, implement, and maintain secure networking across hybrid and multi-cloud (AWS/Azure/GCP). Build secure architectures for containerized applications, apply segmentation and zero-trust, configure cloud-native network controls, deploy IDS/IPS and monitoring, investigate incidents, remediate vulnerabilities, and automate security policy enforcement using IaC, CI/CD, and Python scripting. Mentor engineers and influence platform security strategy.

Lead cybersecurity engineering to embed supply chain integrity and DevSecOps across build, artifact, and deployment pipelines. Define end-to-end provenance, signing, attestation, and automated policy-as-code controls. Secure cloud-native platforms, container and IaC artifacts, and AI-assisted workflows. Partner with risk, infosec, and audit, report residual risk, and build and mentor a security engineering team and developer security champions.