AI Governance Leader

Position Overview

The AI Governance Specialist will lead the strategic development and implementation of comprehensive lifecycle frameworks ensuring consistent execution while maintaining safety, compliance, and regulatory adherence across the organization.

Key Responsibilities

• Develop a standardized AI Lifecycle process for various AI project types: Design and implement lifecycle frameworks for internally built AI solutions, 3rd party AI models, and productivity platform use cases.
• Risk-Based Differentiation: Create tiered governance approaches based on risk levels, including low-risk self-service paths and high-risk comprehensive review processes.
• Cross-Functional Integration: Partner with Data & AI organization, CIO, Architecture, SSRE, Legal, Compliance, ERM and Third-Party Risk teams to ensure comprehensive lifecycle coverage.
• Approval Process Design: Evolve the Gen AI review board process.
• Checkpoint Implementation: Define and implement multiple governance checkpoints with clear governing criteria for each stage.
• Documentation Standards: Lead the development of comprehensive documentation requirements, reference guides, and alignment to existing policies, standards, and controls.
• GCP Integration: Integrate AI governance frameworks with Google Cloud Platform services and other enterprise platforms.
• Oversee the vendor selection and implementation of an AI Governance system, to instrument the AI life cycle activities and signoffs and manage the inventory and AI portfolio reporting.
• Knowledge Management & Enablement: Build and maintain a centralized repository of AI governance resources, best practices, and guidance materials.
• Process Instrumentation: Implement measurement and tracking systems for governance process effectiveness and adoption.
• Change Management: Lead organizational change initiatives to drive adoption of AI governance frameworks across business units.
• Compliance & Risk Management: Ensure AI governance frameworks meet current and emerging regulatory requirements, partnering with legal and compliance.
• Risk Assessment: Develop and maintain risk identification processes and automated approval pathways for appropriate use cases, in partnership with ERM and other risk governors.
• Vendor Management: Create governance frameworks for third-party AI solutions and ensure routines are implemented to achieve regulatory compliance.
• Performance & Value Tracking: Establish and monitor key performance indicators for governance framework adoption and effectiveness.
• Value Measurement: Develop methodologies to track and report on the business value delivered through governed AI implementations.
• Continuous Improvement: Drive iterative enhancement of governance processes based on feedback and performance data.
• Benefits: This role offers a unique opportunity to shape the future of AI governance and contribute to the development of cutting-edge technology.