Description

Key Responsibilities

Architect and implement security frameworks for AI/ML platforms (model hosting, inference endpoints, training pipelines, agentic AI).

Develop and enforce identity, authentication, and authorization (IAA/IAM) controls, ensuring least‑privilege access and secure token flows (OAuth 2.0, OBO, managed identities).

Conduct threat modeling and risk assessments using OWASP AI Top 10, MITRE ATLAS, and NIST AI RMF.

Harden AI supply chain components (model registries, MCP servers, API gateways, third‑party integrations).

Define IAM policies and RBAC for AI environments across Azure, AWS, and GCP.

Collaborate with data science, engineering, and compliance teams to embed security guardrails into the AI lifecycle.

Author security documentation (architecture records, risk assessments, implementation guides).

Monitor evolving AI threat vectors (prompt injection, tool poisoning, model manipulation, data exfiltration) and implement actionable controls.

Present findings and recommendations to leadership and governance boards.

Contribute to enterprise AI security standards and policies.

Required Qualifications

7+ years in cybersecurity, with 3+ years in security architecture/engineering.

Strong knowledge of network, application, and data security; zero‑trust principles.

Hands‑on IAM experience (Azure AD/Entra ID, Okta, Ping, AWS IAM).

Expertise in authentication/authorization protocols (OAuth 2.0, OIDC, SAML, SCIM).

1–3 years of experience securing AI/ML systems (LLM deployments, agentic frameworks, ML pipelines).

Familiarity with AI threat vectors (prompt injection, data poisoning, model inversion, plugin abuse).

Exposure to AI governance frameworks (NIST AI RMF, EU AI Act, OWASP AI Top 10, MITRE ATLAS).

Excellent communication skills; ability to translate technical risks into business language.

Preferred Qualifications

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).

Familiarity with API gateway security for AI services (Azure APIM, Kong, Cloudflare AI Gateway).

Knowledge of secure MLOps pipeline design, container security, and model scanning.

Certifications: CISSP, CCSP, CISM, Azure Security Engineer Associate, or AI‑specific credentials.

Experience with Model Context Protocol (MCP) security controls.

Contributions to security communities, mentoring, or publishing research

Key Skills

Education

Any Gradute