Description

Architect and enforce security frameworks for AI/ML platforms, including model hosting, inference endpoints, and training pipelines.

This role is on-site.

Responsibilities

• Develop and enforce identity, authentication, and authorization controls using OAuth 2.0, OIDC, SAML, and SCIM across Azure, AWS, and GCP.
• Conduct threat modeling and risk assessments using OWASP AI Top 10, MITRE ATLAS, and NIST AI RMF.
• Hardened AI supply chain components including model registries, MCP servers, API gateways, and third-party integrations.
• Define IAM policies and RBAC for AI environments, ensuring least-privilege access and secure token flows.
• Monitor evolving AI threat vectors such as prompt injection, tool poisoning, and data exfiltration, implementing actionable controls.

Required Skills

• 7+ years in cybersecurity with 3+ years in security architecture or engineering.
• 1–3 years of experience securing AI/ML systems, including LLM deployments and agentic frameworks.
• Hands-on IAM experience with Azure AD/Entra ID, Okta, Ping, or AWS IAM.
• Strong knowledge of network, application, and data security with zero-trust principles.
• Familiarity with AI threat vectors like model inversion, data poisoning, and plugin abuse.
• Exposure to AI governance frameworks including NIST AI RMF, EU AI Act, OWASP AI Top 10, and MITRE ATLAS.
• Ability to translate technical risks into business language for leadership and governance boards.

Preferred Skills

• Experience in financial services or regulated industries (SOX, GDPR, MiFID II).
• Hands-on with Microsoft Azure/M365 security ecosystems (Entra ID, Copilot Studio, Defender for Cloud, Purview).
• Certifications: CISSP, CCSP, CISM, Azure Security Engineer Associate, or AI-specific credentials.

Key Skills

Education

Any Gradute