SVP, AI Deployment & Solution Leader

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed.  We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One.

Job Description

The SVP, AI Deployment & Solutions Leader is responsible for driving the organization's AI deployment, solution architecture, and enablement strategy. This executive leader owns and governs the end-to-end AI lifecycle, ensuring AI investments are translated into scalable, secure, and measurable business outcomes.

A primary responsibility of this role is serving as the enterprise's leading authority on AI platforms, architecture, and deployment strategy. The successful candidate will possess deep expertise in Microsoft Azure AI services (primary platform) and AWS AI capabilities, enabling them to advise business and technology leaders on platform selection, technical solution design, architectural patterns, and implementation approaches. This leader will help teams move AI initiatives beyond proof of concept by establishing robust, enterprise-grade architectures that support scalability, reliability, security, governance, and long-term operational success.

The SVP will establish enterprise standards, architectural principles, governance frameworks, and enablement programs that accelerate AI adoption while ensuring alignment with business objectives, risk requirements, and technology strategy. This role partners closely with executive stakeholders across Product, Technology, Operations, Risk, Compliance, and the Business to maximize the value of AI investments across the organization.

Role Overview

In this role, you will:

• Serve as the organization's senior AI deployment and solutions architecture leader, providing strategic and technical direction on AI platforms, services, models, and implementation approaches.
• Guide business and technology teams in evaluating AI opportunities, selecting the appropriate technologies, and designing scalable AI solutions.
• Establish enterprise architectural standards and reusable design patterns for AI applications, ensuring solutions can scale beyond pilots and proofs of concept.
• Provide expert guidance on Azure AI and AWS AI platforms, including AI Foundry, Azure OpenAI, Azure Machine Learning, Amazon Bedrock, and related services.
• Define and govern a unified enterprise AI technology stack aligned with data, security, governance, and cloud strategies.
• Oversee deployment of highly available, secure, compliant, and resilient AI solutions in production.
• Drive enterprise AI adoption through training, best practices, self-service capabilities, and technical enablement programs.
• Lead and develop a multidisciplinary team of AI architects, ML engineers, platform engineers, data scientists, and technical specialists.

Key Responsibilities

Enterprise AI Solutions, Architecture & Technical Advisory for AI Enablement & Acceleration

• Serve as the enterprise's primary advisor on AI solution architecture, platform strategy, technical feasibility, and deployment approaches.
• Provide deep technical leadership across Microsoft Azure AI services and AWS AI platforms, helping teams select the most appropriate technologies, models, and architectures to solve business problems.
• Review and recommend scalable architectural designs that enable AI solutions to move from experimentation into enterprise-wide production deployment.
• Establish reusable architecture patterns, reference designs, and implementation standards for Generative AI, Agentic AI, Machine Learning, and Intelligent Automation solutions.
• Provide guidance on solution tradeoffs, platform selection, model selection, integration patterns, security requirements, and operational considerations.
• Evaluate emerging AI technologies and define adoption strategies aligned to business value, risk tolerance, and long-term technology objectives.
• Partner with business and technology leaders to shape AI use cases, solution roadmaps, and implementation strategies.

AI Enableme