Remote AI Product Manager — Claims & Automation

Sedgwick; Wichita (KS); Remote; USD 120,000 - 170,000; Full time

Benefits offered by this job

Equal Opportunity Employer

Job summary

Sedgwick in the United States is seeking a Product Manager / Product Owner – AI to own end-to-end AI initiatives for a claims domain. You’ll collaborate with business stakeholders to translate operations pain points into structured AI-enabled improvements and sprint-ready plans.

In this role you’ll balance strategic initiative shaping with hands-on backlog ownership, working with AI engineers and data scientists to ensure feasible, compliant, and measurable outcomes that reduce cycle times,

Qualifications

• 6–10 years of experience in Product Management or Business-Technology roles within insurance, claims, or managed services.
• Strong understanding of claims operations, adjustor 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

• End-to-end ownership of AI initiatives for a line of business or platform.
• Define AI-enabled improvements to claims operations, cost control, and client service.
• Backlog ownership and collaboration with AI engineers and data scientists.
• Ensure AI solutions are practical, compliant, and measurable in impact.
• Communicate progress and risks to stakeholders; monitor adoption after deployment.

Skills

6–10 years experience

Insurance domain knowledge

Agile delivery

Translate operational pain into tech

Stakeholder communication

Job description

Sedgwick in the United States is seeking a Product Manager / Product Owner – AI to own end-to-end AI initiatives for a claims domain. You’ll collaborate with business stakeholders to translate operations pain points into structured AI-enabled improvements and sprint-ready plans.

In this role you’ll balance strategic initiative shaping with hands-on backlog ownership, working with AI engineers and data scientists to ensure feasible, compliant, and measurable outcomes that reduce cycle times,