About the role

Senior Assistant Vice President- AI Security Engineering

This is a senior leadership role responsible for defining, embedding, and scaling secure-by-design engineering practices across AI, ML, GenAI, and Agentic AI solutions delivered to global clients. This role ensures that AI platforms and client solutions are secure, resilient, compliant, and production-grade, while balancing innovation speed, regulatory requirements, and enterprise risk posture. The AVP partners closely with engineering, data science, platform, cloud, product, legal, and client leadership teams to operationalize secure AI at scale.

Demonstrated ability to lead secure AI engineering at enterprise and multi-client scale
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

Responsibilities

Define and lead the Secure AI Engineering practice across enterprise and client-delivered AI solutions.

Establish secure-by-design standards, guardrails, and engineering controls for ML, GenAI, LLM, RAG, and Agentic AI systems
Translate regulatory and risk requirements into practical engineering standards aligned with business outcomes.
Oversee security architecture for the end-to-end AI lifecycle—data ingestion, training, fine-tuning, model management, inference, APIs, integrations, and infrastructure.
Ensure protection against advanced AI threats including data poisoning, model theft, prompt injection, inference attacks, agent misuse, hallucination exploitation, and supply-chain compromise.
Drive adoption of secure reference architectures, reusable components, and hardened AI pipelines across delivery teams.
Embed security controls into CI/CD, MLOps, and LLMOps pipelines to enable scale without friction.
Partner with cyber security and IR teams on AI-related incident preparedness, response, and post-incident improvements.

Client Advisory & External Engagement

Act as a trusted advisor to business and clients on secure AI architecture, risk posture, and regulatory readiness.
Lead or support AI security reviews, architecture assessments, and risk discussions for strategic clients.
Build strong internal capability in secure AI engineering and adversarial ML awareness.

Qualifications

Masters DegBachelor’s or Master’s degree in Computer Science, Cyber Security, AI/ML, Data Science, or related field
10–15+ years of experience in cyber security, secure architecture, or platform engineering, with 3+ years focused on Agentic, AI/ML or GenAI environments
Strong hands-on understanding of cloud-based AI platforms (Azure, AWS, GCP or equivalent)
Experience or strong working knowledge of AI governance, privacy, and MLOps/LLMOps tooling (e.g., Credo.ai, Priva Sapien, model registries, and monitoring tools)
Deep knowledge of Secure AI & adversarial ML, Privacy-by-design and data protection, Secure MLOps / LLMOps practices
Familiarity with frameworks and regulations such as NIST AI RMF, NIST CSF, ISO/IEC standards, Emerging global AI regulations (US, EU, sector-specific)
Experience supporting clients in highly regulated industries strongly preferred (preferred) 14 Years