Senior Product Manager, Credit, Fraud & Identity AI Agent (Hybrid)

We are building the next generation of AI-Native operations experiences for credit and fraud teams. As the Sr. Product Manager for Credit, Fraud and Identity, you will own the strategic vision, discovery process, roadmap definition, and end-to-end delivery of AI-powered agents and case management workflows across our Phoenix-based squad and global co-development partners.

This is a high-ownership, high-ambiguity role for a PM who is as comfortable shaping AI capabilities alongside Engineering teams as they are aligning senior stakeholders across time zones. You will translate complex credit and fraud operations needs into AI-native, scalable experiences that improve analyst speed, decision accuracy, and auditability – starting from an MVP and evolving with real operational feedback

Your Mission

Lead the discovery and planning for AI-Native credit and fraud Operations AI Agents. These agents will be part of Case Management experiences that consolidate relevant information, reduce manual work, and increase the speed, accuracy, and explainability of credit decisions and fraud investigations.

This is a hybrid position requiring two days per week onsite at our Scottsdale office. You will report to the Senior Director of Product Management.

You will have opportunity to:

• Define and lead the product vision, roadmap, and delivery for AI-powered credit, fraud, identity, and case management experiences.
• Lead product discovery to identify operational pain points, user needs, and opportunities to improve decision speed, accuracy, and auditability.
• Manage product backlogs, priorities, and sprint goals in partnership with Design, Engineering, and technical leadership.
• Coordinate product development across global teams to align team goals, technical dependencies, and user experience standards.
• Facilitate discussions and workshops across teams.
• Partner with Engineering and ML teams to design AI agents, prompts, retrieval approaches, and workflow automation solutions.
• Define success metrics, evaluation frameworks, guardrails, and human review processes for AI features in regulated environments.
• Evaluate AI platform and architecture options based on cost, performance, governance, and value.