Job description

BASIC FUNCTION The AI / Agentic Product Owner is responsible for post-release ownership and continuous optimization of agentic AI products. This role ensures that deployed AI solutions deliver ongoing business value through effective backlog management, prioritization, and cross-functional coordination. The Agentic Product Owner serves as the primary decision-maker for live AI products, translating feedback, performance signals, and business needs into prioritized work. This role partners closely with AI Enablement, AI Trainers, engineering, and business stakeholders to continuously refine agent behavior, improve outcomes, and scale AI capabilities. This role also requires a foundational understanding of generative AI concepts (e.g., LLMs, RAG, prompt behavior) to effectively manage AI-driven backlogs and product decisions. ESSENTIAL DUTIES AND RESPONSIBILITIES Own Post-Release Product Lifecycle - Own and manage the post-release product backlog for agentic AI solutions - Continuously evaluate product performance and identify improvement opportunities - Ensure AI products evolve in alignment with business objectives and user needs - Drive ongoing optimization of AI capabilities after launch Backlog Management and Prioritization - Intake and triage feedback, bugs, and enhancement requests from stakeholders - Define, prioritize, and maintain a clear, actionable backlog - Balance competing priorities across defect resolution, AI performance improvements, and new features - Lead release planning and prioritization decisions for live AI products - Translate post-release feedback, usage patterns, defect trends, and business needs into prioritized backlog items - Make backlog trade-off decisions across multiple live agentic AI products, balancing urgency, business value, user impact, and delivery capacity Cross-Functional Coordination - Act as the central point of coordination across business stakeholders, engineering and QA teams, AI Enablement, and AI Trainers - Translate post-release feedback, business needs, and operational improvement opportunities into clear product requirements, user stories, and acceptance criteria - Ensure alignment on priorities, timelines, and expected outcomes - Coordinate with business SMEs, content owners, AI Enablement, AI Trainers, engineering, and QA to ensure backlog items are well understood and actionable - Facilitate prioritization discussions where feedback, defects, content gaps, AI behavior concerns, and enhancement requests compete for delivery capacity AI Performance and Feedback Integration - Collaborate with AI Trainers and AI Enablement to incorporate AI behavior analysis and performance insights into backlog decisions - Incorporate feedback into backlog prioritization - Ensure improvements are driven by user feedback, usage patterns, and quality issues - Leverage AI Trainer and AI Enablement expertise for analysis of agent behavior, prompt sensitivity, grounding issues, response quality, and improvement opportunities - Ensure AI-related issues are appropriately categorized, such as product defect, content gap, prompt/behavior issue, user experience gap, or training/adoption need Product Decision Ownership - Serve as the primary decision-maker for product direction, prioritization, and trade-offs - Ensure clear ownership of product outcomes post-launch - Own decisions regarding what gets fixed, enhanced, deferred, or escalated for live AI products - Partner with business sponsors and stakeholders to ensure post-release product decisions remain aligned to business value, user impact, and roadmap priorities Support Scalable Operating Model - Enable a distributed ownership model with clear backlog accountability per AI product - Contribute to scalable practices for managing multiple concurrent AI products - Effectively manage a portfolio of multiple live agentic AI products (typically 2–4 concurrently), balancing priorities across them - Help mature repeatable practices for intake, triage, prioritization, release planning, product health reviews, and transition to steady-state support JOB QUALIFICATIONS Education - Bachelor’s Degree or equivalent experience Preferred: - Business, Technology, or related field - MBA or advanced degree Experience - 7 years in Product Ownership, Business Analysis, or related roles - Experience working in Agile environments - Experience coordinating across business, technology, QA, and operational stakeholders Preferred Experience - Experience working with AI/ML-enabled products or intelligent automation - Familiarity with AI behavior evaluation, prompt iteration, or model output analysis - Foundational understanding of generative AI concepts such as LLMs, retrieval-augmented generation (RAG), and prompt-driven workflows - Experience in platform, SaaS, or enterprise product environments - Experience translating user feedback, performance data, or support trends into actionable product improvements Key Skills - Strong prioritization and decision-making capability - Ability to manage ambiguity in AI-driven systems - Excellent communication and stakeholder influence - Analytical thinking and problem solving - Collaboration across business and technical teams - Foundational understanding of how generative AI systems behave, including variability, hallucination risk, and prompt sensitivity - Strong judgment in balancing user feedback, business value, AI quality concerns, and technical feasibility - Ability to distinguish between product issues, content gaps, AI behavior issues, defects, and user adoption needs - Ability to influence stakeholders and drive alignment without direct authority - Comfort operating in a developing AI product model where standards, ownership, and practices continue to mature Our Interview Practices To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process. Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process. Compensation: $85,600.00 - $149,400.00 USD This role is eligible for Bonus. Compensation range listed is based on primary location of the position. Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location. Your recruiter can share more information about the specific offer for the job location during the hiring process. Additional Information : Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to: Medical, Dental, & Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave. Full details of our benefits are available upon request.

Requirements

Must-haves

This role also requires a foundational understanding of generative AI concepts (e.g., LLMs, RAG, prompt behavior) to effectively manage AI-driven backlogs and product decisions.
Own Post-Release Product Lifecycle
Own and manage the post-release product backlog for agentic AI solutions
Continuously evaluate product performance and identify improvement opportunities
Ensure AI products evolve in alignment with business objectives and user needs
Drive ongoing optimization of AI capabilities after launch
Backlog Management and Prioritization
Intake and triage feedback, bugs, and enhancement requests from stakeholders
Define, prioritize, and maintain a clear, actionable backlog
Balance competing priorities across defect resolution, AI performance improvements, and new features
Lead release planning and prioritization decisions for live AI products
Translate post-release feedback, usage patterns, defect trends, and business needs into prioritized backlog items

Nice-to-haves

Business, Technology, or related field
MBA or advanced degree
Experience working in Agile environments
Experience coordinating across business, technology, QA, and operational stakeholders
Experience working with AI/ML-enabled products or intelligent automation
Familiarity with AI behavior evaluation, prompt iteration, or model output analysis
Foundational understanding of generative AI concepts such as LLMs, retrieval-augmented generation (RAG), and prompt-driven workflows
Experience in platform, SaaS, or enterprise product environments
Experience translating user feedback, performance data, or support trends into actionable product improvements
Strong prioritization and decision-making capability
Ability to manage ambiguity in AI-driven systems
Excellent communication and stakeholder influence

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiagileml

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Parental Leave