Mission Support the client’s AI Security Governance Program by defining, operationalizing and continuously improving the cybersecurity control framework for AI, GenAI and agentic AI use cases.
The role will work with security, architecture and business teams to ensure AI initiatives are registered, assessed, governed and secured across their lifecycle.
The profile will act as the cybersecurity subject matter expert for AI governance, complementing the project manager and helping translate AI-related risks into practical controls, processes,.
AI security governance framework Define and mature the security governance model for AI systems, including intake, registration, risk classification, control mapping, approvals, exceptions, monitoring and periodic reassessment.
Align the governance model with recognized frameworks such as NIST AI RMF, NIST Generative AI Profile, ISO/IEC 42001, OWASP Top 10 for LLM Applications, and local relevant ruling as EU AI Act obligations where applicable.
NIST’s GenAI Profile was released to help organizations manage unique generative AI risks; ISO/IEC 42001 provides a structured AI management system standard; OWASP tracks LLM-specific risks such as prompt injection, insecure output handling, data poisoning and supply-chain vulnerabilities.
AI use case risk assessment Assess AI and GenAI use cases from a cybersecurity perspective, covering: Access control and identity context Agentic AI permissions and tool execution Logging, monitoring and incident response Model exposure and misuse risk Prompt injection and indirect prompt injection Sensitive data leakage Data classification and data residency Model supply chain and third-party AI services Human oversight and approval workflows Security-by-design requirements for AI applications 3.
Control design and operationalization Translate risks into practical security controls, including policies, technical requirements,.