NDS AI Integration Product Owner
Role details
Job location
Tech stack
Job description
Collaboration & Stakeholder Engagement
- Engage stakeholders to understand needs and prioritize AI/automation features by value, risk, and feasibility.
- Communicate requirements, progress, value, and AI assumptions/limitations at the right level of detail.
- Partner with users and SMEs to define actionable requirements and testable acceptance criteria, including quality, safety, and compliance expectations.
- Report status, blockers, and risks (data, model, compliance) to the Product Manager and escalate as needed.
Product Strategy & Roadmap
- Partner with the Product Manager to maintain product vision and strategy for AI-enabled capabilities (agentic AI, workflow automation, decision support).
- Support roadmap planning aligned to strategy, release plans, and measurable outcomes (time saved, quality, cost, compliance).
- Promote transparent delivery and decision-making, including how AI performance is evaluated and monitored.
- Build domain and solution context (data sources, constraints, dependencies, risks, goals) to ensure deliverables meet user needs.
Backlog & Delivery Management
- Own and prioritize the backlog; break AI work into clear epics/stories, including data readiness, evaluation, and rollout.
- Maintain backlog visibility and clarity with a definition of done that includes testing, metrics, and required documentation (e.g., model/release notes).
- Track development progress and readiness; coordinate demos, acceptance, releases, and post-release AI monitoring.
Team Leadership & Change Management
- Strong stakeholder influence skills, ability to influence adoption without direct authority
- Lead or participate in agile ceremonies and help balance discovery, experimentation, and delivery.
- Clarify priorities, outcomes, and tradeoffs; coordinate with delivery teams, data science, security, and operations.
- Drive adoption of AI-enabled practices across delivery teams through communication, training coordination, and feedback loops, in addition to feature delivery.
Financial Awareness
Help monitor investment and ROI; support cost/benefit analysis for AI and automation (tools, licensing, infrastructure, operations)., This role collaborates across business, IT, data science, security/compliance, and leadership. The AI PO drives day-to-day delivery readiness, supports AI product strategy alignment, and partners with the Product Manager on roadmap, stakeholder engagement, and outcome reporting.
Starting pay range for this role is $100,000 - $120,000 based on experience.
This position requires work in support of the Company's contract with the United States Department of Education ("ED"). As such, the United States Government requires that any applicant for this position must complete United States Government security clearance. Effective June 1, 2018, ED has informed Nelnet that security clearance applications for foreign nationals are not being accepted or processed. In light of this direction from ED, Nelnet will be unable to hire applicants without United States citizenship for such positions.
Requirements
- Experience: Product Owner/Manager (or similar) experience in agile; delivery of technology products with cross-functional teams.
- Skills: Strong communication, leadership, and stakeholder management; strong analytical/problem-solving; able to explain AI tradeoffs and limitations to technical and non-technical audiences.
- SDLC Expertise: Working knowledge of modern software delivery practices (branching strategies, CI/CD, code review, sprint cadences, and delivery metrics) and the ability to apply them to drive consistent, measurable delivery outcomes across development teams.
- AI & Automation Acumen : Familiarity with agentic AI patterns (multi-step reasoning, tool-calling, orchestration) and the risk controls needed to govern autonomous actions in development workflows. Hands-on experience with AI-assisted development tools (Copilot, Cursor, AI-driven testing, or prompt-based automation) and the ability to write testable acceptance criteria for AI features, including non-deterministic behavior, guardrails, and fallback conditions.
- Education: Bachelor's degree or equivalent experience.