AIGovernanceLeader

## Accountabilities Lead enterprise AI governance advisory engagements, defining frameworks, policies, and operating models that enable responsible and scalable AI adoption across complex organizations: Conduct AI ecosystem and maturity assessments to identify governance gaps and design tailored frameworks aligned to industry, regulatory, and strategic goals Own multi-workstream client programs, building executive alignment and long-term governance roadmaps tied to AI value realization Define AI governance structures including decision rights, risk tiers, approval workflows, and cross-functional operating models Establish AI FinOps and cost governance guardrails covering spend visibility, budgeting thresholds, tool approvals, and TCO management Design governance metrics, dashboards, and reporting systems tracking risk, value, cost, and control effectiveness Facilitate executive workshops and advisory sessions to drive alignment and decision-making across stakeholders Partner with engineering and platform teams to ensure governance frameworks are implementable within modern AI and data ecosystems Support business development efforts, shaping solutions, proposals, and positioning around AI governance offerings Requirements: Bring deep expertise in AI, data governance, and executive advisory work, with the ability to translate complex AI systems into practical governance models: 10+ years of experience in AI, data, or analytics consulting, including executive-facing advisory roles Proven track record designing governance frameworks, including risk tiering, model oversight, and approval processes Experience building operating models with governance bodies, roles, and RACI structures for enterprise organizations Strong understanding of GenAI concepts, agentic workflows, and enterprise AI use cases Familiarity with AI governance standards such as NIST AI RMF, EU AI Act, or ISO/IEC 42001 Working knowledge of modern AI and data platforms (e.g., Snowflake, AWS, and AI model