The posting
Objective of the Role
The AI Governance Specialist is responsible for designing, implementing, and operating the enterprise AI Governance framework to ensure that artificial intelligence platforms are adopted in a secure, compliant, scalable, and cost-effective manner. Serving as the central governance authority, this role coordinates cross-functional stakeholders—such as Security, Finance, Legal, Risk, DataOps, and Business Units—to establish standard operating models, policies, and lifecycle processes that promote responsible AI usage while safeguarding organizational data, regulatory compliance, and technology investments.
Main Responsibilities
AI Governance Framework
- Design, implement, maintain, and continuously improve the organization's AI Governance Framework.
- Define enterprise-wide AI governance policies, standards, procedures, and operating guidelines.
- Establish governance processes covering AI platform lifecycle management, user onboarding/offboarding, access management, usage monitoring, and exception management.
- Define governance requirements for enterprise AI platforms including ChatGPT, Claude, Gemini, Windsurf/Devin, and future approved AI technologies.
- Take ownership of assigned tasks end-to-end within their defined scope, following through to completion and flagging blockers promptly to the team lead.
AI Inventory & Lifecycle Management
- Maintain the enterprise inventory of AI platforms, AI applications, AI agents, copilots, custom GPTs, models, algorithms, and AI-enabled solutions.
- Establish AI asset registration, ownership, classification, and lifecycle management processes.
- Ensure AI assets remain properly documented and governed throughout their lifecycle.
AI Risk & Compliance
- Conduct pre-deployment risk assessments for all new AI use cases.
- Establish governance controls rooted in Responsible AI principles.
- Monitor adherence to corporate policies, emerging AI regulations, and manage remediation for governance gaps.
- Facilitate internal and external audits concerning AI governance practices.
AI FinOps & Platform Governance
- Partner with FinOps to optimize AI licensing, token consumption, and platform utilization.
- Define governance standards for AI license allocation and consumption monitoring.
- Support forecasting enterprise AI consumption and platform growth.
- Analyze usage trends and recommend optimization opportunities.
Cross-functional Governance - Act as the main governance point of contact to ensure alignment across stakeholders by coordinating enterprise AI activities with:
- Information Security
- IAM
- Enterprise Architecture & AI Architecture
- Legal & Compliance
- Privacy
- Finance
- Risk Management
- DataOps
- Procurement
- Data & AI Transformation
- Business Units
AI Standards & Adoption
- Develop governance of playbooks, standards, templates, and best practices.
- Support enterprise AI adoption through governance enablement.
- Deliver awareness sessions regarding AI governance policies.
- Promote responsible AI adoption across business and technology teams.
Metrics & Reporting - Define KPIs for AI Governance maturity.
- Monitor governance adoption of metrics.
- Produce executive dashboards on AI platform adoption, compliance, risks, and cost optimization.
- Report governance status to executive leadership.
Required Knowledge and Experience
- Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, Cybersecurity, Business Technology, or related field. Master's degree is preferred.
- 4–6 years of experience in Governance, Risk, Compliance, Data Governance, Information Security, Enterprise Architecture, IT Governance, Technology Program Management, or related disciplines.
- Experience designing or operating enterprise governance frameworks, operating models, or corporate policies.
- Experience coordinating cross-functional initiatives involving multiple technology and business stakeholders.
- Exposure to enterprise AI platforms (e.g., ChatGPT, Claude, Gemini, Microsoft Copilot, GitHub Copilot, Cursor, Windsurf) is preferred.
Technical Knowledge
Strong understanding of:
Generative AI platforms
Enterprise AI operating models
AI Governance principles
Responsible AI
AI lifecycle management
AI platform administration
Identity & Access Management
Risk Management
AI platform licensing models
APIs and AI integrations
AI Agents and Copilots
Working knowledge of:
LLMs
RAG concepts
MCP
AI Assistants
Prompt Engineering
Enterprise AI architectures
Governance & Regulatory Knowledge
- NIST AI Risk Management Framework
- ISO/IEC 42001
- ISO 27001
- ISO 27701
- OECD AI Principles
- EU AI Act
- Responsible AI practices
- Data Privacy regulations (LFPDPPP, GDPR)
- Internal Control and Risk Management frameworks
Desired Certifications (One or more of the following is preferred):
- IAPP Artificial Intelligence Governance Professional (AIGP)
- DAMA CDMP
- ISO/IEC 42001 Lead Implementer or Lead Auditor
- Certified Information Systems Security Professional (CISSP)
- Certified Information Security Manager (CISM)
- TOGAF Foundation
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