Enterprise Senior Lead AI Product Manager- Go to Market

Wells Fargo Bank•Concord, CA

4d•Hybrid

About The Position

Wells Fargo is seeking an Enterprise Senior Lead AI Product Manager - Go to Market (Senior Lead Artificial Intelligence Solutions Consultant), as part of the Digital Capabilities team under Digital Technology & Innovation. You will drive the adoption and delivery of enterprise AI/ML capabilities across the organization. In this role, you will serve as the critical bridge connecting product, engineering, end users, and line-of-business stakeholders. You will shape the go-to-market strategy for AI platform capabilities, driving the adoption of machine learning and predictive AI solutions across both on-premises and cloud environments. Success in this role requires delivering clear guidance, scalable enablement, and strong cross-functional partnerships to support emerging capabilities and maximize value. You will lead platform releases and feature rollouts across business and technology domains, coordinating closely with product and engineering teams to manage technical dependencies, risks, and escalations. Additionally, you will orchestrate onboarding, training, documentation, and support programs that enable teams to seamlessly integrate AI into their development workflows. Maintaining a deep understanding of customer workflows, you will gather insights that inform roadmap priorities, enhance usability, and establish scalable platform patterns. You will also ensure readiness and compliance across governance, security, and responsible AI frameworks. Finally, you will deliver executive-ready communications that highlight adoption trends, business impact, and quality metrics—championing a feedback-driven, customer-centric go-to-market approach that accelerates time to value and scales AI success across the organization.

Requirements

7+ years of Artificial Intelligence Solutions experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
3+ years' experience across product/solution management, program delivery, or technical product ownership for AI/ML platforms, or cloud-native solutions
3+ years hands-on experience with cloud technologies (GCP, or Azure) and container orchestration (Docker, Kubernetes/OpenShift)

Nice To Haves

5+ years of experience across the AI/ML lifecycle, including data management, feature engineering, model development, deployment, monitoring/observability, and model governance and risk management
Proven experience operating within large enterprise environments (regulated industry experience preferred) and building scalable, production-grade platforms
Hands-on expertise with Generative AI and agentic AI frameworks, including LLMs, diffusion models, RAG, and tool-based agents; familiarity with ecosystems such as Azure OpenAI, Hugging Face, LangChain/LangGraph, ADK, and vector databases
Strong experience with MLOps/LLMOps practices and tooling, including model registries, CI/CD pipelines, feature stores, prompt and chain versioning, evaluation frameworks, guardrails, and monitoring
Exceptional communication skills with the ability to translate complex technical concepts into clear, actionable insights and influence senior stakeholders
Working knowledge of modern AI/ML platform components and services, such as Vertex AI, BigQuery, OpenShift, IBM Cloud Pak for Data (CP4D), and distributed model execution platforms
Demonstrated ability to develop and execute executive-level roadmaps and dashboards that clearly articulate business impact, adoption trends, and risk posture
Deep technical acumen with the ability to engage at a detailed level across APIs, SDKs, security controls, data contracts, and system performance
Strong negotiation, stakeholder management, and cross-functional leadership capabilities, with a track record of driving alignment and outcomes across diverse teams

Responsibilities

Act as an advisor to senior leadership in developing a large cross functional team to identify and execute complex artificial intelligence initiatives that span a large line of business
Provide consultation to more experienced leaders in order to recommend solutions which solve business challenges
Lead the strategy and resolution of highly complex challenges ensuring the solution delivers the intended benefits
Leverage Artificial Intelligence expertise to evaluate technological readiness, data availability, and resources required to execute the proposed solutions
Provide direction on key issues which may arise during development or implementation
Cultivate relationships with clients to identify and develop a pipeline of future Artificial Intelligence opportunities which align with the strategic priorities of the business
Collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals
Drive the adoption and delivery of enterprise AI/ML capabilities across the organization.
Shape the go-to-market strategy for AI platform capabilities, driving the adoption of machine learning and predictive AI solutions across both on-premises and cloud environments.
Lead platform releases and feature rollouts across business and technology domains, coordinating closely with product and engineering teams to manage technical dependencies, risks, and escalations.
Orchestrate onboarding, training, documentation, and support programs that enable teams to seamlessly integrate AI into their development workflows.
Gather insights that inform roadmap priorities, enhance usability, and establish scalable platform patterns.
Ensure readiness and compliance across governance, security, and responsible AI frameworks.
Deliver executive-ready communications that highlight adoption trends, business impact, and quality metrics.