AI & Data Platform (North Dallas - Hybrid)

Our client is seeking a mid-level Product Manager to help deliver and expand an enterprise AI and data platform supporting multiple areas of the business. This is a hands-on product ownership role for someone who enjoys sitting at the intersection of business, data and engineering. You will work directly with business stakeholders to understand problems and opportunities, translate often-ambiguous requests into clear product requirements, and partner closely with Engineering to deliver solutions through production. The right person does not need to be an AI engineer or data scientist. More importantly, you should be a strong Product Manager who understands data and emerging AI technologies well enough to effectively partner with technical teams, make informed product decisions and drive measurable business outcomes. This role owns the process from business intake and requirements through backlog prioritization, engineering delivery, release, adoption and outcome measurement., Product Ownership & Requirements

• Partner with business stakeholders to understand needs, uncover underlying problems and define desired business outcomes.
• Translate ambiguous or evolving requests into clear problem statements, user stories, acceptance criteria and prioritized requirements.
• Own and maintain the product backlog, ensuring work is properly defined, prioritized and tied to measurable business value.
• Make informed decisions around scope, sequencing, priorities and trade-offs.
• Use SQL or similar tools for light data analysis and profiling to validate assumptions and support product decisions.
• Define success criteria and determine how product impact will be measured following release.

Engineering & Delivery Partnership

• Partner directly with engineers throughout the development lifecycle, from initial requirements through production release.
• Clarify requirements, resolve questions, remove blockers and adjust scope as technical realities emerge.
• Maintain clear Jira stories, acceptance criteria, priorities and delivery status.
• Work effectively with distributed and offshore engineering teams using clear requirements, organized handoffs and strong asynchronous communication.
• Coordinate release readiness, stakeholder communication and rollout plans.

Business Partnership

• Serve as a key connection point between technical teams and stakeholders across functions such as Sales, Finance, Product, Licensing and Operations.
• Build strong relationships with business leaders and subject-matter experts to understand goals, constraints and definitions of success.
• Manage competing priorities and communicate product decisions, timelines and trade-offs clearly.
• Own business requests from initial idea through delivered value.

Adoption & Product Success

• Validate that delivered functionality meets requirements and that data-driven or AI-enabled outputs align with expected results.
• Measure adoption, accuracy, efficiency gains, time savings and other business outcomes following release.
• Help drive adoption and change management, particularly among users who may be hesitant to adopt new technologies or workflows.
• Promote an iterative approach focused on delivering smaller, measurable improvements and learning from user feedback.

• 3-5 years of experience in Product Management, Product Ownership or a blended Product/Business Analyst role.
• Experience supporting data, analytics, enterprise platforms or AI-enabled products strongly preferred.
• Demonstrated ability to gather requirements and turn ambiguous business needs into clear, buildable specifications.
• Strong experience creating user stories, acceptance criteria and prioritized product backlogs.
• Proven experience partnering directly with engineers and owning delivery from intake through release.
• Working knowledge of SQL/data analysis with the ability to validate data and business assumptions.
• Strong hands-on experience with Jira or similar backlog/product-delivery tools.
• Strong stakeholder-management skills and the ability to communicate effectively with both business and technical audiences.
• Experience working with offshore or geographically distributed engineering teams.
• Experience driving user adoption and change management.
• Comfortable working through ambiguity.
• Curious and analytical without needing to be a data scientist.

Nice to Have:

• Exposure to Generative AI, LLM-powered applications or AI agents.
• Familiarity with platforms such as OpenAI, Anthropic Claude, Gemini or similar LLM technologies.
• Experience with Microsoft Azure, Microsoft Fabric, lakehouse/data-platform environments or comparable technologies.
• Understanding of APIs and how applications interact with backend services.
• Familiarity with row-level security, identity-based data access and data-governance concepts.
• Experience using AI-assisted tools to prototype concepts or validate ideas before committing engineering resources.
• Exposure to enterprise business domains such as sales intelligence, finance, licensing/royalties or operations.

• $130,000-140,000 per year