Director of AI Security Engineering

About the role

The Director of AI Security Engineering will build and lead an India‑based function that protects enterprise use of artificial intelligence, including generative AI, copilots, large language models and AI‑enabled SaaS. Reporting to the Senior Director, Data & AI Security in the U.S. and dotted‑line to the Senior Director, Endpoint & Infrastructure Security in India, the role translates global AI security strategy into scalable engineering, control and governance outcomes.

Key responsibilities

• Translate enterprise AI security strategy into India‑based delivery plans, engineering roadmaps and measurable objectives.
• Design and execute security controls for internally developed models, third‑party AI services, SaaS AI features, copilots, retrieval‑augmented generation and AI‑enabled automation.
• Lead AI security architecture across cloud AI services, model integrations, data pipelines and AI‑enabled applications, creating secure design patterns for LLM APIs, vector databases, AI agents and human‑in‑the‑loop controls.
• Define and operationalise controls for prompt injection, data leakage, model misuse, insecure integrations, shadow AI and intellectual‑property exposure.
• Build and lead an India‑based AI security team, developing career paths across architecture, engineering, assurance and technical program management.

Required profile

• 12+ years in cybersecurity, application security, data security, cloud or infrastructure security, or related technology‑risk disciplines.
• 5+ years leading technical cybersecurity or security‑engineering teams.
• Strong understanding of generative AI, machine‑learning platforms, AI‑enabled SaaS, APIs, data pipelines and enterprise cloud architectures.
• Experience defining security controls for high‑risk or emerging technology platforms and translating risk into practical architecture and engineering outcomes.

Required skills

• Generative AI and Large Language Model (LLM) security
• Vector databases and embeddings
• Cloud platforms (Azure, AWS, GCP)
• AI security architecture and secure design patterns
• Prompt‑injection mitigation and AI risk management frameworks (e.g., NIST AI RMF, ISO 27001)