AI Product Owner

AI CoE Delivery Enablement is seeking an experienced Product Owner to lead discovery and execution across two AI mini-pods, delivering two scalable, production-ready AI use cases within a 3 4 month timeframe.

The Product Owner will ensure solutions:

• Leverage established enterprise AI technology standardsAre architected for scalability, reuse, and enterprise adoption

• Align with business-aligned AppDev teams

• Establish repeatable AI delivery patterns

• Enable pod and AppDev team self-sufficiency in ongoing agile execution

This role extends beyond feature delivery and is responsible for positioning each use case for long-term enterprise adoption and sustainable ownership.

The Product Owner will operate across two concurrent AI mini-pods and support use cases delivered under varying engagement models:

• AI CoE led build Mini-pod leads discovery and execution end-to-end

• Joint delivery (co-build) Shared ownership with business AppDev team

• Advisory enablement AppDev team leads build with AI CoE providing standards, guidance, and oversight

The Product Owner must flex across these models while maintaining delivery discipline and alignment with enterprise AI standards.

• Lead structured discovery workshops with business stakeholders

• Validate problem statements and define measurable business outcomes and KPIs

• Translate business objectives into scalable AI solution scope

• Identify data dependencies, technical constraints, and integration points

• Define a clearly bounded, production-ready scope aligned to a 3 4 month delivery window, with explicit in-scope and out-of-scope capabilities

• Define and maintain feature backlog including:

  • Business requirements

  • AI capabilities

  • Non-functional requirements (security, performance, explainability, compliance)

  • Clear acceptance criteria tied to business outcomes

• Prioritize backlog based on value, feasibility, and dependency alignment

• Continuously refine and groom backlog across both mini-pods

• Structure work to accommodate experimentation (e.g., technical spikes, model evaluation cycles)

• Lead agile ceremonies:

  • Sprint planning

  • Backlog refinement

  • Sprint reviews

  • Retrospectives

• Act initially as de-facto Scrum Master

• Track sprint goals, delivery progress, and impediments

• Coordinate cross-team and cross-functional dependencies

• Ensure sprint outcomes align with defined business value

• Ensure alignment with enterprise AI architecture, governance, and risk standards

• Partner with architecture, data governance, and security stakeholders

• Identify and mitigate risks related to:

  • Data quality

  • Model performance

  • Bias and explainability

  • Operationalization and monitoring

• Establish strong working relationships with business-aligned AppDev teams

• Align backlog, technical design, and delivery approach with downstream system requirements

• Define and execute structured handoff and transition plans

• Ensure documentation and knowledge transfer support long-term maintainability

• Enable AppDev teams to adopt AI CoE patterns and standards

• Establish lightweight, outcome-driven agile practices suitable for short AI initiatives (5 7 sprints)

• Develop reusable templates and playbooks, including:

  • Discovery frameworks

  • Backlog structures

  • Sprint reporting standards

  • AI use case delivery playbooks

• Coach pod team members to rotate into Scrum Master role

• Drive progressive ownership transfer by final sprint

• Engagement Duration: 6 9 months

• Target Start Date: End of February / Early March

Phase 1 Mini-Pod 1 (Active): Lead discovery, delivery, backlog development, sprint execution, stakeholder alignment, and governance coordination.

Phase 2 Mini-Pod 2 (Late Q2 / Early Q3 Activation): Expand responsibilities to support concurrent or staggered delivery across both pods, including discovery, execution oversight, and cross-pod coordination.

Engagement may be extended based on delivery outcomes or enterprise scaling needs.

• Location Requirement: Hybrid St. Paul, MN

• Position Type: W2 / C2C

• Work Authorization: As required