Product Owner (AI)

Locations:

• Pittsburgh, PA


• Glenview, IL


• Raleigh, NC


• Austin TX


• Houston TX


• Dallas TX


• Jersey Village TX


• Phoenix AZ

Responsibilities:

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  AI Product Strategy & Use-Case Identification

  
  


• Partners with business leaders and functional stakeholders to identify, evaluate, and prioritize opportunities where AI, Generative AI, Machine Learning, and Intelligent Automation can create measurable business value.


• Understand business processes, pain points, data availability, and operational requirements to determine appropriate AI solutions.


• Translate strategic business objectives into actionable AI product roadmaps, capabilities, and use cases.


• Evaluate potential AI initiatives based on business impact, feasibility, scalability, data readiness, implementation effort, and expected ROI.


• Define MVP scope and support iterative development from proof-of-concept through production deployment and enterprise adoption.


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  Product Ownership & Agile Delivery

  
  


• Own and manage the AI product backlog, ensuring priorities remain aligned with business objectives and product strategy.


• Translate business requirements into detailed epics, features, user stories, acceptance criteria, and functional requirements.


• Continuously prioritize and refine the backlog based on business value, technical feasibility, stakeholder feedback, and evolving organizational priorities.


• Work closely with Scrum Masters, engineering teams, data scientists, AI/ML engineers, architects, and business stakeholders throughout the product lifecycle.


• Participate in Agile ceremonies including sprint planning, backlog refinement, sprint reviews, demos, and retrospectives.


• Define clear acceptance criteria and validate that delivered solutions meet business requirements before release.


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  AI / GenAI Solution Development

  
  


• Partner with Data Science, AI/ML, engineering, and architecture teams to develop solutions leveraging technologies such as Generative AI, Large Language Models (LLMs), Machine Learning, NLP, predictive analytics, AI agents, and Intelligent Automation.


• Help translate business requirements into appropriate AI capabilities and workflows.


• Support evaluation of AI outputs for accuracy, relevance, reliability, usability, and business value.


• Define appropriate product and model performance metrics and establish feedback mechanisms for continuous improvement.


• Work with technical teams to address issues such as hallucinations, model performance, data quality, scalability, and integration with enterprise applications.


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  Business Value & Product Performance

  
  


• Establish measurable KPIs, success criteria, and business outcomes for AI initiatives.


• Develop business cases and help quantify potential improvements in productivity, revenue, cost reduction, customer experience, forecasting accuracy, cycle time, and operational efficiency.


• Monitor adoption and performance after deployment and identify opportunities for continuous improvement.


• Gather feedback from users and stakeholders and incorporate insights into future product releases.


• Communicate AI product performance, risks, dependencies, roadmap progress, and business outcomes to leadership and key stakeholders.


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  Responsible AI & Governance

  
  


• Ensure AI solutions are developed and deployed in alignment with organizational Responsible AI, security, privacy, data governance, and compliance standards.


• Partner with appropriate governance, security, legal, risk, and technology teams throughout the AI product lifecycle.


• Support evaluation of AI solutions for potential bias, accuracy, explainability, data quality, privacy, and other risks.


• Establish appropriate human-in-the-loop controls and monitoring mechanisms where required.


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  Required Qualifications

  
  


• 3–6+ years of experience in Product Management, Product Ownership, Business Analysis, Digital Transformation, Agile Delivery, or a related discipline.


• Demonstrated experience owning or supporting technology products from business problem identification through implementation and adoption.


• Experience translating complex or ambiguous business requirements into structured product requirements, user stories, and acceptance criteria.


• Strong understanding of Agile/Scrum product development methodologies and backlog management.


• Working knowledge of AI, Machine Learning, Generative AI, LLMs, analytics, or Intelligent Automation technologies.


• Ability to work effectively with Data Scientists, AI/ML Engineers, Software Engineers, Architects, and business stakeholders.


• Strong analytical and problem-solving capabilities with an ability to connect technical capabilities to measurable business outcomes.


• Excellent stakeholder management, facilitation, communication, and presentation skills.


• Experience using product and delivery tools such as Jira, Azure DevOps, Confluence, or similar platforms.


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  Preferred Qualifications

  
  


• Previous experience working within Supply Chain, Sales, Commercial Operations, or related business functions.


• Experience delivering AI/ML or GenAI products in an enterprise environment.


• Understanding of AI/ML concepts including model evaluation, training and inference, data pipelines, prompt engineering, RAG, and LLM-based applications.


• Familiarity with technologies such as Python, SQL, Snowflake, Azure/AWS/GCP AI services, APIs, and modern data platforms.


• Experience developing business cases, ROI assessments, and value-realization frameworks for AI or digital initiatives.


• Experience taking AI solutions from proof-of-concept/MVP to scalable production deployment.


• Exposure to enterprise AI governance and Responsible AI frameworks.

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