Director, Cyber Security Architect

This role defines enterprise AI security architecture to protect AI-integrated applications and secure the full AI lifecycle from data pipelines through model training, inference, and deployment. You will establish controls for sensitive data and build defenses against adversarial ML threats.

• Define enterprise AI security architecture including reference architectures and guardrails
• Secure MLOps/ML platforms with identity, secrets management, network segmentation, and least-privilege access
• Establish data protection controls for ingestion, anonymization/pseudonymization, encryption, tokenization, and lineage
• Design adversarial ML defenses including model poisoning, prompt injection, jailbreaking, data leakage, and output manipulation
• Provide cloud security standards and policy-as-code across AWS, Azure, and GCP

You will develop AI security reference architectures, guardrails, and standards spanning secure data pipelines and MLOps/ML platform security. The scope includes identity, secrets management, network segmentation, least-privilege access, key management (KMS/HSM), encryption, tokenization, lineage, and adversarial ML defense controls such as prompt injection and jailbreaking.

The ideal candidate is an experienced enterprise security architect with 12+ years in cybersecurity architecture and at least 3 years focused on AI/ML or data platform security at scale. They can define AI security reference architectures, guardrails, and standards across secure data pipelines, MLOps, and AI-integrated applications. They also bring hands-on knowledge of adversarial ML defenses such as prompt injection and model poisoning, along with cloud security expertise across AWS, Azure, and GCP.