Sr. AI Product Manager

Description

Hyundai Capital America (HCA) helps people move forward. Through Hyundai Motor Finance, Genesis Finance, and Kia Finance, we deliver innovative financing, leasing, and insurance solutions to more than 3 million customers and businesses nationwide.

We're a company driven by growth, innovation, and people. At HCA, you'll find opportunities to build new skills, expand your career, and make a real impact-while working in a diverse, inclusive, and values-driven environment. We're proud to support our communities through volunteerism, philanthropy, and engaged Employee Resource Groups.

If you're looking for a fast-paced, collaborative workplace where your ideas matter, join us as we lead the future of financing freedom of movement. Apply today.

WHAT YOU WILL DO

The Sr. AI Product Manager independently manages the lifecycle of assigned complex AI products, translating business needs into product priorities, requirements, and delivery plans. The role develops and maintains product roadmaps within established business and technology strategy, makes product decisions within assigned scope, and leads cross-functional delivery to achieve measurable business outcomes. Working with architecture, engineering, data, UX, and risk teams, the role drives product quality, adoption, and continuous improvement within established governance and compliance requirements.

HOW YOU WILL MAKE AN IMPACT

• Product Ownership & Delivery
  
  • Manage the lifecycle of assigned complex AI products, from requirements definition through release and ongoing improvement.
  • Translate business needs into product requirements, user stories, acceptance criteria, and measurable success criteria.
  • Own and prioritize product backlogs, balancing business value, user needs, technical dependencies, risk, and delivery capacity.
  • Make product decisions on scope, sequencing, and delivery trade-offs within assigned authority, providing direction and clarification to engineering teams.
  • Lead release planning, stakeholder demonstrations, and rollout readiness in partnership with business and technical teams.
• Product Strategy & Roadmap
  
  • Develop and maintain roadmaps for assigned AI products within established business and technology strategy.
  • Evaluate and prioritize AI use cases, including GenAI copilots, intelligent automation, and decisioning, based on business value, feasibility, risk, and cost.
  • Establish milestones, dependencies, and outcome measures, adjusting roadmap recommendations as business needs and product performance evolve.
  • Balance new capabilities with product stability, scalability, operational efficiency, and cost control.
• AI / GenAI Product Delivery & Performance
  
  • Define product scope and requirements with architects, engineering, and data teams, considering approaches such as retrieval-augmented generation, agents, and model selection.
  • Establish product-level evaluation measures and release criteria with technical and governance partners, incorporating approved AI guardrails.
  • Assess evaluation results and recommend release readiness based on task success, grounded-response rates, and identified product limitations.
  • Use telemetry, user feedback, and experimentation to identify performance issues and prioritize product improvements.
• Cross-Functional Leadership & Alignment
  
  • Lead alignment across business, engineering, data, UX, and governance stakeholders on product priorities, requirements, and delivery commitments.
  • Resolve competing requirements and manage cross-team dependencies, escalating scope, resource, or risk decisions beyond assigned authority.
  • Partner with Legal, Security, Compliance, and Risk to address requirements and issues affecting responsible AI implementation.
  • Communicate product progress, decisions, dependencies, and risks to stakeholders and leadership.
• Adoption & Change Management
  
  • Lead launch, enablement, and change-management planning for assigned AI products with business and delivery partners.
  • Partner with UX, training, and business teams to address adoption barriers through user-experience improvements, training, and communications.
  • Establish and monitor adoption and business-outcome measures, including usage, task success, and operational effectiveness.
  • Translate adoption trends and stakeholder feedback into recommended actions and product backlog priorities.
• Governance & Responsible AI
  
  • Incorporate established AI governance, privacy, security, and Responsible AI requirements