AI Product Owner

ZENITH INFOTEK LLC•Remote, AL

1d•$60 - $70•Hybrid

About The Position

AI Product Manager to lead the development and delivery of AI-driven solutions across key business areas, including Underwriting and Claims. This role will serve as a bridge between business and technology, ensuring that AI use cases are aligned with enterprise strategy and provide measurable business value. The ideal candidate combines strong business analysis skills, technical expertise, and deep domain knowledge in insurance operations.

Requirements

Bachelor’s degree in Business, Technology, Data Science, or a related field; MBA preferred.
8+ years of experience in Product Ownership, Business Analysis, or related roles.
Proven experience in implementing AI/ML or advanced analytics use cases within a business environment.
Excellent business analysis skills, including requirements gathering, process mapping, and documentation.
Strong understanding of Agile methodologies (Scrum, Kanban) and product management best practices.
Technical acumen with the ability to work closely with data scientists and engineers (familiarity with AI/ML concepts, data pipelines, APIs, etc.).
Experience with tools such as JIRA, Confluence, and process mapping tools (e.g., Visio, Lucidchart).
Strong analytical thinking and problem-solving abilities.
Excellent communication and stakeholder management skills, with the ability to influence at all organizational levels.

Nice To Haves

Experience working with enterprise AI platforms or copilots.
Familiarity with data governance, model risk management, and regulatory considerations in insurance.
Experience leading digital transformation initiatives within the insurance industry.

Responsibilities

Own the end-to-end lifecycle of AI products, including vision, roadmap, and use cases, from ideation through implementation and scaling.
Translate business, clinical, operational, and research stakeholder needs into product roadmaps, technical solutions, PRDs, epics, user stories, KPIs, release plans, and adoption strategies.
Lead cross-functional teams—including developers, integration engineers, analysts, architects, QA/UAT teams, vendors, and other partners—through ambiguity, competing priorities, and complex enterprise environments.
Develop clear product requirements, user stories, and acceptance criteria based on business needs.
Create and maintain product roadmaps aligned with enterprise strategic priorities.
Prioritize backlogs and plan sprints collaboratively with data science, engineering, and delivery teams.
Map processes in detail and identify opportunities for optimization via AI and automation.
Ensure successful implementation and adoption of AI solutions, including change management and stakeholder communication.
Monitor product performance, define KPIs, and drive continuous improvement based on insights and feedback.
Collaborate closely with technical teams to ensure feasibility, scalability, and seamless integration with existing systems.
Support and enhance enterprise AI platforms by aligning use cases and capabilities with business needs.