SVP, AI Governance

Synchrony•Stamford, CT

3d•$200,000 - $330,000•Hybrid

About The Position

Help Synchrony scale AI responsibly by leading the enterprise AI Governance function and driving the operating discipline, controls, oversight routines, and execution capabilities required to manage AI risk across the organization. As the SVP of AI Governance, you will report to the Chief AI Officer and lead the design, implementation, and ongoing management of Synchrony’s AI governance activities and ongoing management of Synchrony’s AI first-line of defense risk management and governance activities. You will serve as a key first-line leader accountable for translating AI strategy, policy, regulatory expectations, and risk framework requirements into practical governance processes, durable controls, measurable standards, and repeatable execution routines. This role will work in close partnership with second-line and third-line stakeholders to strengthen Synchrony’s AI risk management framework, support independent challenge and assurance, prepare for regulatory and oversight activities, and ensure the organization can demonstrate disciplined governance across the AI lifecycle. You will also partner closely with engineering, program management, legal, compliance, risk, information security, model risk management, supplier management, business owners, and technology leaders to ensure key AI governance capabilities are delivered, adopted, documented, monitored, and continuously improved. You are a strategic governance leader who can operate at the intersection of AI, technology delivery, risk management, controls, regulatory readiness, and enterprise execution. You bring sound judgment, strong executive presence, structured problem solving, stakeholder influence, and the ability to convert complex and evolving AI risk expectations into clear processes, controls, accountabilities, and outcomes.

Requirements

Bachelor’s degree in a related discipline and 10+ years of experience in risk management, technology governance, AI governance, data governance, compliance, audit, controls, regulatory readiness, technology delivery, or strategic program leadership; in lieu of a degree, 12+ years of relevant experience.
Proven experience leading governance, risk, control, compliance, or oversight programs in a complex enterprise environment.
Strong understanding of AI, generative AI, agentic AI, machine learning, automation, data, technology platforms, and responsible AI concepts sufficient to lead governance across technical and non-technical stakeholders.
Experience designing or operating governance frameworks, control frameworks, lifecycle processes, risk tiering processes, approval workflows, inventories, monitoring routines, issue management, or assurance-ready reporting.
Experience partnering with second-line risk and compliance functions and third-line audit or assurance teams in a regulated environment.
Demonstrated ability to translate policy, standards, regulatory expectations, risk frameworks, and audit findings into practical operating models, procedures, controls, evidence routines, and execution plans.
Strong stakeholder management and influencing skills, with the ability to align senior leaders, technology teams, control partners, business owners, and delivery teams around shared governance outcomes.
Excellent written and verbal communication skills, including executive-level storytelling, regulatory-ready documentation, concise risk articulation, and the ability to simplify complex AI governance topics.
Strong execution discipline with experience managing complex initiatives, dependencies, risks, milestones, and cross-functional deliverables.
Data-driven orientation with experience defining governance metrics, control performance indicators, risk reporting, adoption measures, and continuous improvement insights.
Comfort operating in ambiguity and at pace, with strong judgment, prioritization, resilience, and the ability to bring structure to fast-moving AI governance work.
Ability and flexibility to travel for business as required

Nice To Haves

Experience in financial services, banking, payments, credit, consumer finance, or another highly regulated industry.
Experience with AI governance, model risk management, technology risk, operational risk, third-party risk management, data governance, information security, privacy, compliance, or internal audit.
Familiarity with AI risk management frameworks, responsible AI principles, regulatory expectations, risk-based controls, model validation concepts, supplier oversight, and audit evidence practices.
Experience with enterprise governance tools, GRC platforms, workflow tools, AI or model inventories, technology control repositories, reporting dashboards, SharePoint, Jira, ServiceNow, Power BI, or similar platforms.
Experience building governance capabilities for generative AI, agentic AI, AI platforms, AI gateways, AI control planes, model registries, agent registries, evaluations, monitoring, logging, or policy enforcement.
Demonstrated ability to establish a new enterprise function, mature an existing governance capability, or drive a transformation agenda across multiple functions and lines of defense.

Responsibilities

Lead Synchrony’s enterprise AI Governance function within the AI Office, including the operating model, governance routines, standards, controls, reporting, and oversight activities needed to scale AI responsibly.
Help drive the design, implementation, and continuous improvement of Synchrony’s AI governance framework in alignment with enterprise risk management expectations, AI policy and standards, regulatory requirements, and industry practices.
Partner closely with second-line risk, compliance, legal, technology risk, model risk management, supplier management, privacy, information security, and other control partners to strengthen AI risk management processes and ensure clear ownership across the lines of defense.
Partner with third-line Internal Audit and other assurance stakeholders to prepare for ongoing monitoring, reviews, audits, evidence requests, issue management, and validation of AI governance processes and controls.
Define and execute the strategy for key AI governance topics, including AI intake, use case registration, risk tiering, inventory management, approval workflows, lifecycle gates, control validation, monitoring, recertification, and exception management.
Lead the development of new AI controls and control enhancements, ensuring requirements are practical, risk-based, measurable, auditable, and embedded into delivery processes wherever possible.
Translate AI policy, standards, and regulatory expectations into actionable procedures, job aids, playbooks, control requirements, decision frameworks, and governance artifacts for use by technology teams, business owners, and control partners.
Maintain a disciplined enterprise view of AI use cases, tools, agents, models, patterns, approvals, risk ratings, ownership, lifecycle status, control evidence, and governance outcomes.
Prepare for regulatory activities, executive oversight, audits, and risk reviews by developing high-quality materials, evidence packages, issue responses, remediation plans, and executive-ready updates.
Responsible for leading direct 1LoD risk management and governance interaction with regulators.
Lead governance reporting for the Chief AI Officer and senior stakeholders, clearly articulating portfolio status, risk themes, control maturity, regulatory readiness, open issues, dependencies, decisions needed, and progress against governance priorities.
Work closely with AI engineering, architecture, security, cloud, data, and platform teams to ensure technical governance capabilities such as registries, gateways, policy enforcement, logging, monitoring, evaluation, guardrails, and evidence generation are delivered on track.
Partner with program management to ensure governance initiatives are planned, prioritized, resourced, sequenced, tracked, and executed with clear milestones, dependencies, owners, risks, and escalation paths.
Support the intake and review of AI use cases and patterns, helping teams understand applicable requirements, required approvals, risk implications, control expectations, and paths to responsible delivery.
Ensure AI governance processes differentiate appropriately across internal productivity use, business process transformation, customer-facing capabilities, third-party AI solutions, agentic AI, model-like use cases, and high-risk or regulated activities.
Coordinate with legal, compliance, and regulatory change stakeholders to monitor emerging AI laws, rules, standards, and supervisory expectations, and to translate applicable requirements into governance actions.
Drive continuous improvement of AI governance capabilities by identifying gaps, simplifying processes, improving transparency, reducing friction, strengthening evidence quality, and helping the organization move faster while staying within risk appetite.
Perform other duties and/or special projects as assigned