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Strong employer brand and metro location but niche senior AI-security role moderates applicant density.
Highly domain-specific AI security and regulated-environment expectations limit cross-industry transferability.
Mandatory 10+ years, specialized AI-security skills, and regulatory/enterprise experience create high shortlisting strictness.
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Design, validate, and embed security controls for AI platforms, GenAI applications, LLM integrations, RAG pipelines, AI agents, and AI workflows across design, build, deployment, and operations.
Lead AI-specific threat modelling, adversarial testing, attack surface reviews, risk documentation, and mitigation planning for enterprise AI systems.
Improve AI security metrics, automate controls, provide reusable security guidance, and support governance including standards, patterns, and compliance frameworks application.
10+ years of experience in cybersecurity, security architecture, application security, cloud security, AI/ML security, or enterprise security engineering.
Strong hands-on experience securing AI, ML, GenAI, LLM applications, RAG pipelines, AI agents, model APIs, or enterprise AI platforms.
Deep understanding of AI-specific threats including prompt injection, jailbreaks, model poisoning, data leakage, model exfiltration, and AI supply chain risks.
Working knowledge of security frameworks and standards such as OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, Responsible AI, and relevant regulatory expectations.
Proven hands-on AI security expert able to lead secure architecture reviews, threat modelling, control design, testing, and practical risk mitigation for enterprise AI environments.
Experience collaborating across multiple teams including cybersecurity, platform engineering, cloud, data, AI, architecture, compliance, risk, and automation in a complex global setup.
Ability to translate AI security risks into scalable, enterprise-ready technical controls while balancing governance with practical delivery.