Product Manager AI

Sedgwick•St. David's, NV

1d•Remote

About The Position

The Product Manager / Product Owner – AI owns AI initiatives end to end for a specific Line of Business or claims domain. The role partners with business stakeholders to define AI-enabled improvements to claims operations, cost control, and client service performance, then translates objectives into structured, sprint-ready execution plans. Combining strategic initiative shaping with hands-on backlog ownership, the role collaborates daily with AI engineers and data scientists. It ensures AI development addresses real operational pain points and that delivered solutions are practical, compliant, and measurable in impact. The position works with claims leadership, operational managers, and Business Transformation Leads, and balances operational urgency with disciplined backlog governance, including when client escalations or regulatory deadlines create pressure for rapid change.

Requirements

6–10 years of experience in Product Management or Business-Technology roles within insurance, claims, or managed services.
Strong understanding of claims operations, adjuster workflows, or insurance servicing models.
Experience working in Agile delivery environments.
Ability to translate operational pain points into structured technical requirements.
Strong stakeholder communication skills across business and technical audiences.

Responsibilities

Work with claims leadership, operational managers, and Business Transformation Leads to identify workflow bottlenecks, leakage drivers, customer friction points, regulatory risks, and client performance commitments.
Translate operational insights into defined AI use cases with measurable objectives, such as reducing claim cycle time, improving reserving accuracy or fraud detection, and speeding up document processing.
Break initiatives into epics and features reflecting operational workflows, accounting for system integrations, adjuster behavior, client reporting requirements, and compliance obligations.
Collaborate with AI engineers and data scientists to validate feasibility, data availability, model explainability considerations, and downstream operational impact.
Own and continuously refine the product backlog, prioritizing it according to business value and enterprise AI portfolio constraints.
Prepare user stories with detailed acceptance criteria grounded in claims scenarios and operational realities.
Stay engaged with the delivery team during sprints, clarifying claims processes, regulatory rules, and client-specific variations.
Validate that models, automation features, and decision-support tools work within claims workflows and meet user expectations.
Communicate progress, risks, and trade-offs transparently to Line of Business stakeholders and manage expectations about sequencing and delivery timelines.
After deployment, monitor adoption, operational metrics, and user feedback, and adjust backlog priorities based on real-world performance and measurable impact.
Balance operational urgency with disciplined backlog governance when client escalations or regulatory deadlines create pressure for rapid change.