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Product Manager/Owner AI

External
Sedgwick logoSedgwick · Telecommuter, TN
Full-timeRemoteToday
AgileComplianceLeadership
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Responsibilities

  • This role requires balancing operational urgency with disciplined backlog governance, particularly in environments where client escalations or regulatory deadlines may introduce 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
  • #LI-TS1 #remote
  • Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace.

Benefits

Remote work options

Additional Information

By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve. Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies Certified as a Great Place to Work® Fortune Best Workplaces in Financial Services & Insurance Product Manager/Owner AI End-to-End AI Product Owner - Line of Business or Platform Aligned Role Overview The Product Manager / Product Owner - AI is responsible for end-to-end ownership of AI initiatives for a specific Line of Business or claims domain. This role partners directly with business stakeholders to define AI-enabled improvements to claims operations, cost control, and client service performance, and translates those objectives into structured, sprint-ready execution plans. This role combines strategic initiative shaping with hands-on backlog ownership and daily collaboration with AI engineers and data scientists. It ensures that AI development is grounded in real operational pain points and that delivered solutions are practical, compliant, and measurable in impact.


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