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Wells Fargo · 2 days ago

COO AI COE Program Initiative Leader – Business Execution Director

SAN FRANCISCO, CA

Full-time

Hybrid

Senior Level, Lead/Staff

$185K/yr - $300K/yr

8+ years exp

Wells Fargo is a global leader in financial services, committed to driving innovation and helping customers succeed. They are seeking an AI Program Initiative Leader to manage program governance for Generative and Agentic AI initiatives across the Chief Operating Office, ensuring responsible AI adoption and operational excellence.

BankingFinancial ServicesFinTechInsurancePayments

No H1B

Responsibilities

Manage and develop multiple business functional areas with focus on implementing and delivering long-term strategies, policies, and process advancements for cross-functional stakeholders, and internal and external partners associated with the area of Business Execution or who are affected by its outcomes

Identify Business Execution opportunities and strategies for process improvement and risk control development over the long-term to ensure operational excellence and process efficiency

Lead Business Execution team for assigned initiatives ensuring solutions are designed, integrated, and controlled to improve effectiveness, limit risk exposure, and create efficiencies as appropriate

Interpret and develop a range of policies and procedures for long-range and fundamental retooling of perspective, approach, culture, quality, relationships, operations, and capabilities

Collaborate and influence functional management to obtain resources, influence outcomes, address conflict, and ensure alignment with Wells Fargo strategies or policies and business line objectives

Manage allocation of people and financial resources for Business Execution

Develop and guide a culture of talent development to meet business objectives and strategy

Partner with the Enterprise Gen AI program and IRM to implement oversight requirements, dimension risk profiles for fit for purpose oversight processes, and develop responsible guardrails for “citizen development” of AI

Refine the target operating model across COO and its partners responsible for implementing and maintaining AI Solutions

Build and implement fit-for-purpose procedures to monitor, change, and decommission AI Solutions post implementation

Ensure changes to the AI Risk Management Policy, Model Risk Management Policy, and other related policies (e.g., SDLC, Data Management) are properly adopted into COO methodologies, procedures, and management routines

Ensure proper change communication and awareness exists to AI Product Executives for changes to enterprise or COO expectations

Qualification

AI Program LeadershipModel Risk ManagementAI GovernanceBusiness ExecutionData ManagementStrategic PlanningProcess ImprovementTalent DevelopmentCommunication Skills

Required

8+ years of Business Execution, Implementation, or Strategic Planning experience, including Management or leadership experience, or equivalent experience demonstrated through one or a combination of the following: work experience, training, military experience, education

4+ years of management or leadership experience

Preferred

8+ years of experience in Strategy, Program Leadership and/or Program Governance focused on developing new or emerging capabilities/ functions/ business models that are Enterprise in nature or Divisional in nature

Senior leadership experience operating and implementing at scale against the Software Development Lifecycle, Data Management best practices, Model Risk Management, and/or with Artificial Intelligence / Intelligent Automation Solutions

Strong expertise in AI and model governance, including model lifecycle oversight, risk tiering, approval authorities, ongoing monitoring, and model decommissioning

Experience developing, deploying, and continuously evolving common operating practices across a large organization

Experience assessing and mitigating AI-specific risks, including model bias and fairness, explainability, data quality and lineage, privacy, cybersecurity, and third-party risk

Demonstrated success operationalizing Responsible AI principles—such as transparency, accountability, fairness, robustness, and appropriate human oversight—within regulated banking environments

Familiarity with policy and regulatory change management and quality control frameworks

Strong understanding of the bank regulatory landscape as it relates to models, data, and emerging technologies, including expectations from U.S. and global regulators

Experience developing and maintaining AI- and model-related policies, standards, control requirements, and documentation designed to meet regulatory and audit scrutiny

Familiarity integrating AI governance controls into SDLC, MLOps, Data Governance, and Technology Risk Management processes

Ability to succinctly and simply communicate complex subjects to senior executives and external parties, where appropriate