Enterprise AI Platform – Predictive AI Product Manager

Wells Fargo Bank•Charlotte, NC

7h•Hybrid

About The Position

About this role: Wells Fargo is seeking an Enterprise AI Platform – Predictive AI Product Manager (Lead Artificial Intelligence Solutions Consultant), as part of the Digital Capabilities team under Digital Technology & Innovation. Learn more about the career areas and lines of business at wellsfargojobs.com. We are seeking a highly technical and business‑savvy Product Manager to build and scale core platform capabilities for our Enterprise Predictive AI Platform, spanning on‑premise infrastructure and public cloud environments including Google Cloud and Microsoft Azure. In this role, you will own the delivery and adoption of enterprise AI/ML capabilities across the organization, ensuring they drive meaningful and measurable business outcomes. You will serve as the connective tissue between product, engineering, data science, risk, and line‑of‑business stakeholders—shaping solution strategy, enabling foundational platform capabilities, orchestrating complex platform migrations, and ensuring AI solutions are delivered securely, scalably, and in compliance with enterprise standards. The ideal candidate combines deep technical expertise with strong stakeholder leadership to accelerate the organization’s ability to realize value from AI at scale. In this role, you will:

Requirements

5+ years of Artificial Intelligence Solutions experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of experience in product management, solution management, program delivery, or technical product ownership, with a focus on AI/ML platforms, APIs, and/or cloud-native solutions
5+ years of experience across the AI/ML lifecycle, including data management, feature engineering, model development, deployment, monitoring/observability, and model governance and risk controls
2+ years of hands-on experience with public cloud technologies (Google Cloud Platform and/or Microsoft Azure) and container orchestration (Docker, Kubernetes, OpenShift)

Nice To Haves

Demonstrated experience leading technology governance initiatives related to resiliency, risk management, and regulatory execution within large-scale banking or financial services organizations
Excellent communication and executive presence, with the ability to influence senior stakeholders and translate complex technical concepts into clear, actionable insights
Proven success operating in large enterprise environments—preferably within regulated industries—and building platforms and capabilities at scale
Experience with MLOps and LLMOps practices and tooling, including model registries, CI/CD pipelines, feature stores, prompt/chain/versioning, evaluation frameworks, guardrails, and monitoring
Working knowledge of enterprise platform components and services such as Vertex AI, BigQuery, OpenShift, IBM Cloud Pak for Data (CP4D), and large-scale distributed model execution platforms (e.g., NX1 or equivalent)
Proven ability to develop and execute executive-level roadmaps, dashboards, and reporting that clearly demonstrate business impact and risk posture
Strong technical depth, with the ability to dive into APIs, SDKs, security controls, data contracts, and performance and reliability considerations
Strong negotiation, stakeholder engagement, and cross-functional leadership skills, with a track record of driving alignment and execution across teams

Responsibilities

Lead a team to identify, strategize and execute highly complex Artificial Intelligence initiatives that span a line of business
Recommend business strategy and deliver Artificial Intelligence enabling solutions to solve business challenges
Define and prioritize cases, obtain the required resources and ensure the solutions deliver the intended benefits
Leverage Artificial Intelligence expertise to evaluate technological readiness and resources required to execute the proposed solutions
Make decisions to drive the implementation of Artificial Intelligence initiatives and programs while serving multiple stakeholders
Resolve issues which may arise during development or implementation
Collaborate and consult with peers, colleagues and managers to resolve issues and achieve goals