\\\\Why Wells Fargo\\\\ \\\\Are you looking for more? Find it here.\\\\ At Wells Fargo, we're more than a financial services leader were a global trailblazer committed to driving innovation, empowering communities, and helping our customers succeed. We believe that a meaningful career is much more than just a job its about finding all of the elements to help you thrive, in one place. Living the Well Life () means youre supported in life, not just work. It means having robust benefits, competitive compensation, and programs designed to help you find work-life balance and well-being. Youll be rewarded for investing in your community, celebrated for being your authentic self, and empowered to grow. Join us! \\\\About this role:\\\\ Wells Fargo is seeking a \\\\Senior Lead Digital Product Manager GenAI Testing Strategy & Release Management Lead\\\\ to join the Chief Operating Office (COO) Artificial Intelligence Center of Excellence (AI COE). This Senior Lead role is accountable for defining, governing, and executing \\\\enterprise-wide testing strategy and release management\\\\ for Generative AI and Agentic AI solutions across the firm. The role focuses on ensuring disciplined, compliant, and scalable delivery through robust testing frameworks, coordinated release trains, and strong lifecycle governance aligned to Wells Fargos Responsible AI standards. As a senior individual contributor with broad organizational influence, this role operates with significant autonomy and decision-making authority and partners closely with technology teams, product leaders, risk and control partners, and lines of business to ensure AI capabilities are production-ready, resilient, and compliant before release. \\\\In this role, you will:\\\\ \\+ Act as a senior advisor to leadership on AI testing strategy, release readiness, and execution risk across complex, enterprise-wide initiatives. \\+ Define and own end-to-end testing strategy for GenAI and Agentic AI solutions, including functional, non-functional, integration, model, security, resilience, and risk-based testing. \\+ Establish and oversee AI test governance, ensuring testing approaches align to enterprise risk standards, Responsible AI principles, and regulatory expectations. \\+ Design and manage release management frameworks and release trains to enable coordinated, predictable deployment across multiple teams, platforms, and lines of business. \\+ Lead execution planning for testing and release activities across scaled delivery models, including Agile and SAFe environments. \\+ Partner closely with Risk, Compliance, Legal, Control Management, and Model Risk teams to ensure solutions meet governance and control requirements prior to production. \\+ Identify, assess, and mitigate testing and release risks for highly complex and ambiguous AI initiatives. \\+ Develop and socialize release readiness criteria, go/no-go decision frameworks, and post-release validation processes. \\+ Ensure continuous improvement of testing practices through metrics, defect analysis, post-incident reviews, and lessons learned. \\+ Translate complex technical, operational, and regulatory requirements into clear testing plans and release execution strategies. \\+ Provide thought leadership and guidance on emerging best practices for AI testing, deployment controls, and lifecycle management. \\+ Influence, coach, and mentor delivery teams and peers, setting standards for quality, accountability, and execution excellence consistent with Senior Lead expectations. \\\\Required Qualifications:\\\\ \\+ 7+ years of digital product management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education \\\\Desired Qualifications:\\\\ \\+ Extensive experience leading enterprise-scale testing and release management for complex digital or AI capabilities. \\+ Strong experience delivering Generative AI and/or Agentic AI solutions, preferably within highly regulated environments. \\+ Deep expertise in AI lifecycle management, including testing strategies, deployment controls, monitoring, and post-release optimization. \\+ Proven experience establishing and managing release trains across multiple teams and platforms. \\+ Strong understanding of risk-based testing, model validation considerations, data controls, and non-functional testing requirements. \\+ Demonstrated knowledge of Responsible AI principles, AI governance, and model risk management practices. \\+ Experience partnering with Risk, Compliance, Legal, Control, and Technology teams to deliver compliant, production-ready solutions. \\+ Strong executive communication and influencing skills, with the ability to drive alignment across matrixed organizations. \\+ Ability to operate independently and make sound judgments consistent with Senior Lead individual contributor accountability. \\+ Familiarity with Agile, SAFe, or other scaled delivery methodologies in large enterprise environments. \\\\Job Expectations:\\\\ \\+ This position is \\\\NOT\\\\ eligible for Visa sponsorship. \\+ Ability to work on site per Wells Fargo's standard operating model in the listed location (hybrid schedule 3 days on-site & 2 remote) \\+ The ability to travel up to 10% of the time. \\\\Posting Location:\\\\ \\+ Charlotte, NC \\+ Dallas, TX \\+ Irving, TX \The Global Operations functions adhere to a location strategy; therefore, your candidacy may be determined based on your current location. Remote work locations are not available for these\\ \\\\Posting End Date:\\\\ 6 Apr 2026 \\\\\\\Job posting may come down early due to volume of applicants.\\\\\ \\\\We Value Equal Opportunity\\\\ Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic. Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business units risk appetite and all risk and compliance program requirements. Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process. \\\\Applicants with Disabilities\\\\ To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo () . \\\\Drug and Alcohol Policy\\\\ Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy () to learn more. \\\\Wells Fargo Recruitment and Hiring Requirements:\\\\ a. Third-Party recordings are prohibited unless authorized by Wells Fargo. b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process. \\\\Req Number:\\\\* R-533208

The role requires 7+ years of digital product management experience, or equivalent demonstrated through work experience, training, military experience, or education. Desired qualifications include extensive experience leading enterprise-scale testing and release management for complex digital or AI capabilities. Strong experience delivering Generative AI and/or Agentic AI solutions, preferably within highly regulated environments, is also sought. Deep expertise in AI lifecycle management, including testing strategies, deployment controls, monitoring, and post-release optimization, is expected. Proven experience establishing and managing release trains across multiple teams and platforms is beneficial. A strong understanding of risk-based testing, model validation considerations, data controls, and non-functional testing requirements is necessary.