Role Purpose

Lead the execution of Guardian’s AI governance program by operationalizing enterprise policies, standards, and guardrails across AI models, copilots, agents, andRAG‑basedworkflows. This role ensures AI governance is consistently implemented, scalable, and embedded into delivery and platform workflows—enabling responsible AI adoption while managing risk.

The AI Governance Lead partners closely with Data Science, AI Platforms, Data Management, Data Governance, Risk, Legal, and Technology teams to translate enterprise AI governance strategy into practical processes, controls, andday‑to‑dayways of working.

Responsibilities 

AI Governance Execution & Program Leadership 

• Lead the execution of Guardian’s AI governance program across analytics, AI, and agentic use cases. 

• Implement enterprise AI governance policies, standards, and guardrails in alignment with defined risk appetite and regulatory expectations. 

• Ensure governance processes are repeatable, risk‑based, and scalable—not bespoke or ad hoc. 

Operating Model & Workflow Integration 

• Own the AI governance operating model, including intake, review, escalation, monitoring, and change management processes. 

• Govern AI model lifecycles and AI system behaviors across models, copilots, agents, and RAG workflows, including retrieval strategies, tool use, actions, and human‑in‑the‑loop requirements. 

• Embed AI governance controls into platforms and delivery workflows so controls are observable, durable, and auditable. 

Standards, Controls & Risk Management 

• Operationalize governance standards for AI development, deployment, monitoring, and retirement. 

• Implement risk‑based controls and escalation paths based on use case type, data sensitivity, and impact. 

• Partner with Risk, Legal, Compliance, and Security teams to ensure AI governance execution meets internal and external requirements. 

Cross‑Functional Partnership 

• Serve as the primary AI governance partnertodata science, analytics, engineering, and product teams.

• Coordinate with Data Management and Data Governance leaders to ensure AI governance aligns with data controls, quality expectations, andAI‑readinessrequirements.

• Support enterprise governance forums by preparing materials, surfacing risks, and enablingtimelydecision‑making.

Measurement & Continuous Improvement

• Define and track operational KPIs for AI governance execution, including coverage, exceptions, monitoring effectiveness, and remediation trends.

• Identifygaps, inefficiencies, and emerging risks; recommend adjustments to processes, controls, and tooling.

• Continuously improve governance mechanisms as AI capabilities and use cases evolve.

Leadership & Influence

• Provide leadership to AI governance practitioners and analysts; set priorities, manage workload, and build governanceexpertise.

• Influence senior stakeholders across business, technology, and risk through strong execution, transparency, and practicalproblem‑solving.

Requirements 

- 12+ years of experience in data, analytics, AI, technology risk, or related disciplines. 

- Demonstrated experience governing AI systems, including models and agentic workflows, at enterprise scale. 

- Strong understanding of AI lifecycle considerations, data usage patterns, and risk management principles. 

- Proven ability to develop and translate strategy into executable standards, workflows, and operating models. 

- Experience influencing senior stakeholders across business, technology, risk, and legal teams. 

- Excellent communication skills and ability to operate through influence rather than direct control.