MLOps & Productionization: Experience building and operating scalable MLOps platforms for AI/ML systems, including model lifecycle management, CI/CD for ML pipelines, feature stores, automated retraining, model monitoring/drift detection, experiment tracking, and deployment orchestration using Kubernetes, MLflow, Kubeflow, SageMaker, or equivalent tooling in high-throughput production environments. • AI Agent Security: Define and implement security controls for autonomous AI agents, including detection of agent drift, unauthorized resource access, prompt injection attacks, privilege escalation, data leakage, and other emerging threats in Agentic AI systems.