AI Cyber Security

Job Description Summary

The AI Security Architect is responsible for designing, implementing, and governing security frameworks and requirements to enable the secure use of AI and related infrastructure. This role ensures AI technologies are developed and deployed securely, ethically, and in compliance with regulatory and organizational requirements. This role will be part of cybersecurity organization with a matrix line to the AI team

• Justification

Justification

New role for conduction security arch reviews of AI projects acting as liaison between ZEDI and Cyber orgs

Hiring Requirements

Key Responsibilities

·       Develop secure-by-design architectures for AI/ML platforms, including data ingestion, model training, model deployment, and inference layers.

·       Define reference security architectures, patterns, and guardrails for secure AI development.

·       Identify threats unique to AI systems—model inversion, poisoning, evasion attacks, data leakage, prompt injection, etc. Evaluate emerging AI security threats, tools, and best practices.

·       Lead AI-specific risk assessments and security design reviews.

·       Work with red teams to validate model robustness against adversarial attacks.

·       Establish security policies for ethical AI use. Ensure compliance with enterprise, industry, and regulatory frameworks (e.g., NIST AI RMF, GDPR, HIPAA, SOC2, ISO 42001).

·       Partner with data science, platform engineering, cloud security, product, and compliance teams.

Required Skills & Qualifications

• 10+ years in cybersecurity architecture or engineering roles.
• Strong knowledge of modern AI/ML architectures, pipelines, and tooling. Experience with LLM security, prompt safety testing, or generative AI governance.
• Understanding of AI based attacks and threats.
• Strong knowledge of data protection and controls required to protect data.
• Knowledge of creating and communicating cybersecurity risks both in technical and non-technical manner.
• Experience working in AI/ML or data engineering environments.
• Proven track record designing enterprise security frameworks or architecture patterns.
• Excellent communication with technical and non-technical stakeholders.
• Strong analytical, problem-solving, and decision-making abilities.
• Leadership skills to guide engineering teams and influence organizational policy.
• Knowledge of regulatory frameworks specific to healthcare or finance (HIPAA, PCI, etc.)