AI Platform Agilist

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

Agilists at U.S. Bank are customer obsessed with a focus on serving product teams, ensuring all product vision, planning and development activities are rooted in Agile and Product Values & Principles. Agilist enables the organization to consistently experiment and evolve business strategy based on prior outcomes and feedback. They drive culture change through day to day to work with a focus on Agile & Product mindset, values and continuous improvement and keep the team focused on achieving product goals using agile methods.

As an Agilist, you will:

Agile Leadership & Coaching

* Champion Agile principles and practices across AI and data-focused teams, driving adoption and continuous improvement []

* Coach product owners, engineers, and business stakeholders on Agile frameworks such as Scrum, Kanban, or SAFe

* Facilitate core Agile ceremonies (sprint planning, stand-ups, reviews, retrospectives) to ensure effective team execution

* Foster a culture of transparency, collaboration, and iterative delivery across cross-functional teams

AI Project Delivery Enablement

* Partner with technical teams (data science, ML engineering) and business leaders to translate AI use cases into actionable backlogs and sprint goals []

* Guide teams in delivering AI/ML solutions iteratively, accounting for experimentation, model training, and validation cycles

* Align delivery plans with business objectives, ensuring AI initiatives provide measurable value []

* Support prioritization of work based on business impact, technical dependencies, and data readiness

Cross-Functional Collaboration

* Enable collaboration across diverse teams, including data scientists, engineers, product managers, and domain experts []

* Remove impediments and escalate risks impacting delivery timelines or outcomes

* Act as a liaison between technical and non-technical stakeholders to ensure shared understanding

* Metrics, Governance, and Continuous Improvement

* Define and track Agile and AI-specific performance metrics (e.g., velocity, cycle time, model performance indicators) []

* Ensure AI delivery adheres to governance, compliance, and ethical standards (e.g., bias, data privacy) []

* Facilitate retrospectives and apply learnings to improve delivery effectiveness and team maturity

* Promote data-driven decision-making and experimentation

Organizational Change & Transformation

* Support enterprise Agile transformation efforts, particularly within AI and digital initiatives

* Influence leaders and stakeholders to adopt Agile ways of working and AI-enabled delivery models

* Drive mindset shifts toward iterative development, experimentation, and continuous learning

Basic Qualifications

* Agile product development, agile coaching, agile portfolio management experience

Skills Should Include

* 8+ years of experience in Agile roles (Agilist, Scrum Master, Agile Coach, or Delivery Lead)

* Proven experience in AI

* Proven experience supporting or leading AI, machine learning, or data-centric projects

* Strong understanding of Agile frameworks (Scrum, Kanban, SAFe)

* Experience working with cross-functional technical teams, including data scientists and engineers

* Demonstrated ability to coach teams and influence stakeholders at multiple levels

* Strong communication, facilitation, and problem-solving skills

* Agile certification (e.g., Certified Scrum Master, SAFe Agilist, ICP-ACC)

* Familiarity with AI/ML lifecycle concepts (model development, training, validation, deployment)

* Experience with AI governance, responsible AI, or model risk management

* Exposure to Agile tools (e.g., Jira, Azure Dev Ops) and data/AI platforms

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