AI Product Owner - Remote, Impactful Backlog Leader

Sedgwick Claims Management Services Ltd; Tennessee; On-site; USD 110,000 - 150,000; Full time

Job summary

Sedgwick, a leading risk and claims solutions provider, seeks a Product Owner - AI to collaborate with Product Managers and data scientists to translate AI initiatives into actionable backlog items and clear acceptance criteria.

You will partner with ML engineers and MLOps teams to ensure alignment with business outcomes, manage stories, and support validation through UAT and performance monitoring. Strong communication and cross-functional collaboration are essential.

Qualifications

• Five years of related experience or equivalent combination of education and experience.
• Experience in business analysis, requirements definition, or supporting product delivery.
• Experience in claims, insurance, healthcare, or other regulated environments preferred.
• Experience working within agile or hybrid delivery teams preferred.
• Experience supporting AI, machine learning, or data-driven product initiatives preferred.

Responsibilities

• Partner with Product Managers on backlog refinement and prioritization.
• Define development-ready stories and acceptance criteria from epics/features.
• Execute delegated Product Manager responsibilities when PM capacity is limited.
• Collaborate with development teams to ensure stories align with business outcomes.
• Support UAT to confirm delivered functionality meets requirements.
• Track delivery metrics and surface risks and dependencies.
• Translate AI/ML capabilities into backlog items with defined thresholds.

Skills

Backlog management

User stories

Agile delivery

Requirements documentation

Cross-functional collaboration

OKR reporting

Budget awareness

Communication skills

Education

Bachelor's degree in Business Administration/Information Systems

Job description

Sedgwick, a leading risk and claims solutions provider, seeks a Product Owner - AI to collaborate with Product Managers and data scientists to translate AI initiatives into actionable backlog items and clear acceptance criteria.

You will partner with ML engineers and MLOps teams to ensure alignment with business outcomes, manage stories, and support validation through UAT and performance monitoring. Strong communication and cross-functional collaboration are essential.