Ic5 - Ai Governance Specialist

Objective of the R ole

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, Data Ops, 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 Chat GPT, 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 Fin Ops & Platform Governance

• Partner with Fin Ops 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
• Data Ops
• 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., Chat GPT, Claude, Gemini, Microsoft Copilot, Git Hub 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