About this role
This amount is what we reasonably believe we will pay for the position; however, offer amounts may vary based on factors such as geographic location, relevant education, experience, qualifications, skills, shift, or any collective bargaining agreements.
For eligible positions, compensation may include participation in a bonus or sales incentive plan, subject to the terms and conditions of the applicable plan documents. For certain sales roles, Wesco also offers a commission structure that provides additional compensation based on sales results, as defined by the applicable commission plan.
In addition, Wesco offers a benefits program for eligible employees, which may include paid time off, medical, dental, and vision coverage, and retirement savings plans. Additional details about benefits are available here.
We are seeking a business focused AI Product Owner to identify, prioritize, and deliver AI and Generative AI solutions that drive business value across the enterprise. This role serves as the connection between business stakeholders, product teams, AI engineers, and technology leadership, transforming business challenges into scalable AI products. The ideal candidate brings product ownership experience, Agile delivery expertise, and a solid understanding of AI, Machine Learning, and Generative AI technologies. Experience supporting Supply Chain, Sales, or Commercial Operations is preferred.
Locations:
• Pittsburgh, PA • Glenview, IL • Raleigh, NC • Austin TX • Houston TX • Dallas TX • Jersey Village TX • Phoenix AZ
Key Responsibilities
AI Strategy & Use Case Development
• Partner with business leaders to identify and prioritize AI, GenAI, ML, and automation opportunities.
• Evaluate business processes, operational challenges, feasibility, scalability, and ROI.
• Translate strategic objectives into AI roadmaps, capabilities, and measurable outcomes.
• Define MVP scope and support projects from concept through adoption.
Product Ownership & Agile Delivery
• Own and manage the AI product backlog, aligning priorities with business goals.
• Convert business needs into epics, user stories, requirements, and acceptance criteria.
• Lead backlog refinement, sprint planning, reviews, demos, and stakeholder engagement.
• Collaborate with technical and business teams to ensure successful delivery and adoption.
• Validate solutions against requirements before release.
AI Solution Delivery
• Partner with technical teams to deliver solutions leveraging GenAI, LLMs, NLP, predictive analytics, AI agents, and automation.
• Translate business requirements into AI capabilities and workflows.
• Define success metrics and evaluate solution effectiveness, usability, and business impact.
• Support continuous improvement through ongoing optimization and enhancements.
Value Realization & Governance
• Establish KPIs tied to productivity, revenue growth, customer experience, and operational efficiency.
• Develop business cases and measure value realization for AI investments.
• Monitor adoption, communicate progress, risks, and outcomes.
• Ensure compliance with Responsible AI, security, privacy, and governance standards.
Required Qualifications
• 3+ years of experience in Product Management, Product Ownership, Business Analysis, Agile Delivery, or Digital Transformation.
• Experience delivering technology solutions from concept through implementation.
• Strong Agile, backlog management, and stakeholder engagement skills.
• Working knowledge of AI, Machine Learning, Generative AI, LLMs, analytics, or automation technologies.
• Ability to translate complex business problems into clear requirements and product plans.
• Strong analytical, communication, facilitation, and presentation skills.
• Experience with Jira, Azure DevOps, Confluence, or similar tools.
• Experience using AI tools such as Claude or similar platforms to develop requirements, prototypes, and documentation.
Preferred Qualifications
• Experience within Supply Chain, Sales, Commercial Operations, or related functions.
• Experience delivering AI/ML or GenAI solutions in enterprise environments.
• Understanding of prompt engineering, RAG, model evaluation, data pipelines, and LLM applications.
• Familiarity with Python, SQL, Snowflake, cloud AI services, APIs, and modern data platforms.
• Experience building AI business cases, ROI models, and scaling solutions from MVP to production.
• Knowledge of Responsible AI and enterprise governance practices.
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