AI Product Owner at PennyMac Financial Services in Cary, NC

Job description

PENNYMAC Pennymac is (NYSE: PFSI) is a specialty financial services firm with a comprehensive mortgage platform and integrated business focused on the production and servicing of U.S. mortgage loans and the management of investments related to the U.S. mortgage market. At Pennymac, our people are the foundation of our success and at the heart of our dynamic work culture. Together, we work towards a unified goal of helping millions of Americans achieve aspirations of homeownership through the complete mortgage journey. A Typical Day The AI Product Owner owns the enterprise semantic layer that represents Pennymac's business. This role defines how core entities are modeled once and reused across origination, servicing, and enterprise AI workflows. The role connects business domain experts, data engineering, architecture, risk and compliance, and the teams building applications and AI agents on top of the ontology. As a Product Owner, you will manage complex initiatives that span multiple integrated business systems and departments. You will create operational efficiencies by designing new business processes, act as a domain expert in end-to-end business functions, and drive technology solutions and workflow optimization across the division. The AI Product Owner will: Define and champion the enterprise ontology product vision, strategy, and roadmap. Own the end-to-end product lifecycle, from ideation, requirements, and prioritization through development, launch, and iteration. Make sure product decisions align with broader strategic initiatives, including revenue opportunities and cost-saving measures identified by product and business leadership. Communicate product strategy, progress, and outcomes to senior management and other stakeholders. Own and prioritize the ontology change backlog. Establish and run the ontology governance process, including change review and approval, impact assessment, and a stewardship model with named owners per domain. Partner with data engineering on hydration: map source systems to object types and confirm pipelines keep the model current. Define competency questions and validation tests for each domain model, confirming the model answers the questions the business actually asks before it ships. Define adoption and quality metrics: reuse across workflows, duplicate or orphaned entity rates, definition coverage, mapping freshness, and time from change request to merged model change. Own the semantic grounding layer for AI and agentic use cases, so agents and LLM-backed workflows reason over governed objects with inherited permissions, lineage, and audit trails rather than raw, ungoverned data. Collaborate with business units, technology teams, and executive leadership to gather insights, align priorities, and ensure product success. Translate business needs into clear goals, user stories, acceptance criteria, and functional requirements using use cases, process flows, and data analysis. Serve as a domain expert for the business functions your product supports: assess current capabilities, find improvement opportunities, and define measurable outcomes. Create and maintain product documentation, including requirements, process flows, and reports. Demonstrate behaviors aligned with the organization's culture and values. What You’ll Bring Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent work experience. 5+ years in product management, business analysis, or data product ownership, including at least 2 years (preferred) in semantic modeling, ontology, taxonomy, canonical data models, or knowledge graphs. Experience taking a domain from undocumented or inconsistent sources through conceptual modeling, formal specification, validation, and production deployment. Working understanding of formal knowledge representation: class hierarchies, property definitions, cardinality, inheritance, logical constraints, and controlled vocabularies. Working knowledge of SQL and