AI/ML Deployment and Enablement Lead

U.S. Bank

AI/ML Deployment and Enablement Leader overseeing the end-to-end AI lifecycle at U.S. Bank.

Posted 6/2/2026full-timeMinneapolis • Illinois, Minnesota • 🇺🇸 United StatesSenior💰 $170,255 - $200,300 per yearWebsite

Tech Stack

Tools & technologies

AirflowAWSAzureCloudElasticSearchERP

About the role

Key responsibilities & impact

Own the enterprise AI feasibility function , providing authoritative guidance on Model selection (traditional ML, GenAI, agentic AI)
Approved platforms, tools, and services
Architectural patterns and trade‑offs
Act as the primary technical advisor to business and technology teams evaluating AI use cases.
Ensure teams are guided toward enterprise-approved solutions that accelerate delivery and reduce long‑term operational risk.
Identify delivery blockers early (data readiness, platform onboarding, governance dependencies) and drive resolution.
Establish and maintain AI playbooks, standards, and best‑practice frameworks for internal teams.
Sponsor and guide enterprise‑wide workshops, training, and knowledge‑sharing initiatives.
Provide consultative guidance on AI solutions and architecture, partnering with product, engineering, and business teams to shape use cases, design patterns, and implementation approaches.
Act as a trusted advisor to teams evaluating AI feasibility, trade‑offs, and architectural alignment with enterprise standards.
Build and lead an AI Center of Excellence to drive talent strategy, mentorship, and continuous capability development.
Provide leadership and oversight for enterprise MLOps practices, including CI/CD, model registry, and automated rollback.
Ensure AI systems meet regulatory, security, and privacy standards in collaboration with risk and compliance stakeholders.
Define and review SLAs, KPIs, and observability standards for AI services, ensuring operational excellence and accountability.
Set the architectural vision for a scalable, modular AI ecosystem spanning data ingestion, feature stores, training infrastructure, and inference.
Champion standards for model governance, including versioning, data lineage, explainability, and auditability.
Evaluate emerging AI technologies and approaches, and define adoption roadmaps aligned with business value and risk tolerance.
Own the strategic evolution of the on‑prem AI platform stack (e.g., Airflow, Elasticsearch) and its operating model.
Ensure delivery of self‑service platforms, APIs, and tooling that enable teams to innovate efficiently and safely.
Partner with cloud, DevOps, and security leaders to balance performance, cost efficiency, scalability, and compliance.

Requirements

What you’ll need

Masters degree or equivalent work experience
Strong hands-on experience delivering AI projects in production, including engineering, deployment, and monitoring of AI use cases
Deep familiarity with Microsoft Azure AI suite and AWS AI offerings, with Azure as the primary platform
Exposure to a wide range of AI platforms, tools, and models, including custom modeling and execution
Experience with AI application delivery and use case development, not just machine learning or data science
Ability to review and provide technical feasibility guidance for AI requests across the enterprise
Leadership and people management skills, ideally with experience managing developers and data scientists
Experience with agentic AI use cases and tools (e.g., LangChain, LangGraph,AI Foundry, Amazon Bedrock, 3rd party agentic capabilities thru vendors in CRM, ERP & other spaces), with deep knowledge to guide what will be more suitable for solving business problems using gen AI models, human agents, and AI agents and suggest strong technical design to promote reuse and scale for value
Familiarity with enterprise-scale AI enablement, including documentation, education, and self-serve approaches

Benefits

Comp & perks

Healthcare (medical, dental, vision)
Basic term and optional term life insurance
Short-term and long-term disability
Pregnancy disability and parental leave
401(k) and employer-funded retirement plan
Paid vacation (from two to five weeks depending on salary grade and tenure)
Up to 11 paid holiday opportunities
Adoption assistance
Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI feasibilitymodel selectionMLOpsCI/CDmodel registrydata ingestionfeature storesinferencecustom modelingAI application delivery

Soft Skills

leadershippeople managementconsultative guidancementorshipcommunicationproblem-solvingtechnical advisoryknowledge sharingcollaborationtraining

Certifications

Masters degree