About this role
The Assistant Vice President - AI Runtime Security will define and own enterprise AI governance controls, focusing on runtime security, monitoring, and enforcement for GenAI, LLM, RAG, and Agentic AI systems in production. The role involves establishing technical standards for threat detection and prevention, including prompt injection, agent manipulation, inference abuse, data leakage, and hallucination exploitation. Responsibilities include ensuring AI runtime architectures incorporate guardrails, policy enforcement points, and telemetry collection across APIs, orchestration layers, and model gateways. The incumbent will oversee continuous monitoring for behavioral anomalies, data and concept drift, and output risk indicators, while institutionalizing governance requirements for risk response, alerting, and automated containment. Collaboration with platform, security, and MLOps/LLMOps teams is essential to embed runtime controls into CI/CD pipelines and deployment workflows. The role also requires leading technical governance for high-risk deployments to ensure compliance with internal policies and global regulatory frameworks like the NIST AI RMF, while acting as a technical advisor for executive stakeholders on production readiness and risk acceptance. Qualifications include a Bachelor’s or Master’s degree in Computer Science, Information/Cyber Security, AI/ML, Data Science, or a related field. Candidates must have 9-12 years of overall experience, including at least 3 years specifically in AI governance, AI runtime threat vectors, and AI observability. Proven ability to design and govern runtime guardrails using platforms like Credo.ai is required, alongside hands-on experience with LLMOps/MLOps tools such as MLflow, Weights & Biases, Datadog, or Azure Monitor. Proficiency in drift detection and AI behavior monitoring using tools like Aporia or Datatron is expected, as is the ability to operationalize governance controls within CI/CD pipelines orchestrated through platforms like Kubeflow, Airflow, or Azure DevOps.