Description
This is a temporary contractor position for an existing vacancy.
Purpose
The AI Governance Specialist ensures that all AI models and related data assets comply with the organization's Enterprise AI Policy, Responsible AI principles, and regulatory obligations (e.g., NIST AI RMF, ISO/IEC 23894, ISO/IEC 42001, EU AI Act, Canada AIDA). This role bridges technical teams and governance bodies to maintain transparency, accountability, and ethical standards across the AI lifecycle.
Key Responsibilities
- Model Governance & Compliance: Register all AI models in the enterprise AI registry; maintain Model Cards, TEVV evidence, fairness/bias assessments; ensure Responsible AI requirements (lawful basis, data minimization, bias testing, explainability, security controls).
- AI Risk Assessments & Management: Conduct AI risk assessments for all AI tools, agents, and systems developed internally or purchased from vendors, using the Enterprise AI Risk Framework; classify each by risk tier, document risks and required controls, and escalate high-risk cases.
- Lifecycle Oversight: Monitor model performance, drift, and compliance with TEVV standards; coordinate periodic attestations for NIST/ISO/EU AI Act readiness; support decommissioning and archival processes.
- Data Stewardship: Validate data lineage, metadata, and quality for AI training datasets; collaborate with Business Data Stewards to enforce data governance policies.
- Policy & Standards Enablement: Act as a subject matter expert for AI governance in development and procurement reviews; provide guidance on Enterprise AI Policy and Data & AI Risk assessment processes, ensuring risk assessments cover all AI systems.
- Training & Awareness: Educate teams on Responsible AI practices, compliance workflows; and governance training modules.
Qualifications
- Bachelor's degree in Data Science, Computer Science, Engineering, or related field; advanced degree preferred.
- 3+ years in AI/ML development AI/ML lifecycle management or AI/ML stewardship
- 3+ years experience of model risk, or risk/compliance management.
- Practical knowledge of AI governance frameworks (NIST AI RMF, ISO/IEC 23894, or ISO/IEC 42001) and emerging regulations (EU AI Act, Canada AIDA).
- Experience with data cataloging and lineage tools and AI platforms; familiarity with TEVV practices.
- Strong understanding of privacy, security, and regulatory compliance in AI contexts (PIA/DPIA, DLP, RBAC).
Skills
- Excellent communication and stakeholder management; ability to translate technical AI concepts into governance requirements.
- Analytical mindset with attention to detail and risk awareness; strong documentation discipline.
- Familiarity with DevOps/ALM controls, audit logging, and service principal usage for secure integrations.
Performance Metrics
- Percentage of AI models registered and compliant with governance standards.
- Timeliness and completeness of risk assessments, attestations, and model documentation.
- Reduction in governance exceptions and audit findings; closure rate of remediation actions.
