Sr. AVP - AI Security Engineering

Strong balance of technical depth, risk judgment, and executive communication. Proven effectiveness operating in global, regulated, client-delivery environments. Credibility with both deeply technical teams and non-technical executive stakeholders.\nQualifications:\nBachelor’s or Master’s degree in Computer Science, Cyber Security, AI/ML, Data Science, or related field.\n15+ years of experience in cyber security, secure architecture, or platform engineering, with 3+ years focused on Agentic, AI/ML or GenAI environments.\nStrong hands-on understanding of cloud-based AI platforms (Azure, AWS, GCP or equivalent).\nExperience or strong working knowledge of AI governance, privacy, and MLOps/LLMOps tooling (e.g., Credo.ai, Priva Sapien, model registries and monitoring tools).\nDeep knowledge of Secure AI & adversarial ML, Privacy-by-design and data protection, Secure MLOps / LLMOps practices.\nFamiliarity with frameworks and regulations such as NIST AI RMF, NIST CSF, ISO/IEC standards, Emerging global AI regulations (US, EU, sector-specific).\nExperience supporting clients in highly regulated industries strongly preferred.\nResponsibilities:\nDefine and lead the Secure AI Engineering practice across enterprise and client-delivered AI solutions.\nEstablish secure-by-design standards, guardrails, and engineering controls for ML, GenAI, LLM, RAG, and Agentic AI systems.\nTranslate regulatory and risk requirements into practical engineering standards aligned with business outcomes.\nOversee security architecture for the end-to-end AI lifecycle—data ingestion, training, fine-tuning, model management, inference, APIs, integrations, and infrastructure.\nEnsure protection against advanced AI threats including data poisoning, model theft, prompt injection, inference attacks, agent misuse, hallucination exploitation, and supply-chain compromise.\nDrive adoption of secure reference architectures, reusable components, and hardened AI pipelines across delivery teams.\nEmbed security controls into CI/CD, MLOps, and LLMOps pipelines to enable scale without friction.\nPartner with cyber security and IR teams on AI-related incident preparedness, response, and post-incident improvements.\nAct as a trusted advisor to business and clients on secure AI architecture, risk posture, and regulatory readiness.\nLead or support AI security reviews, architecture assessments, and risk discussions for strategic clients.\nBuild strong internal capability in secure AI engineering and adversarial ML awareness.