Product Manager, AI Platform
$125,000–$125,000 year
HybridIrving, Texas, United States
Job Summary
Partner with business stakeholders to elicit, challenge, and document requirements for AI-driven features, analytics views, and platform services. Translate vague business requests into clear problem statements, prioritized user stories, and acceptance criteria while owning the product backlog. Own end-to-end delivery, including scope, sequencing, prioritization, trade-offs, and release readiness, collaborating closely with distributed and offshore engineering teams. Serve as the primary contact between the Data & AI Platform team and business domains such as Sales, Finance, Licensing, Product, and Operations. Define acceptance criteria and validate shipped features against source-of-truth data, measuring adoption, accuracy, and business impact post-release. Work during standard U.S. business hours to support predictable releases and drive adoption among reluctant users.
Required Qualifications
- 3-5 years of experience in product management, product ownership, or a blended product/analyst role, ideally supporting data, analytics, or platform products
- Demonstrated ability to translate business needs into clear, buildable, prioritized specifications
- Proven experience partnering with engineers to ship products or features that delivered measurable value
- Comfort working with data, including basic SQL or similar tools for profiling and validating assumptions
- Excellent stakeholder management and communication skills across business and technical audiences
- Demonstrated adoption/change-management experience with user populations that may be reluctant to adopt new technology
- Experience using Jira or similar project-management software to manage backlogs, user stories, priorities, and delivery status
- Bachelor's degree in Business, Computer Science, Information Technology, Data Science, or a related field, or equivalent professional experience
Desired Qualifications
- Practical experience with frontier LLM platforms such as Anthropic Claude, OpenAI, Gemini, or Grok, including prompting and model selection
- Understanding of row-level security, identity-scoped data access, and contractual or intellectual-property constraints around data
- Comfort using AI-assisted development tools to prototype ideas and validate concepts before engineering investment
- Exposure to AI/ML-enabled products, LLM-powered applications, or intelligent agents
- Familiarity with modern cloud data platforms such as Microsoft Fabric/Azure or equivalent lakehouse and semantic-layer environments
- Understanding of API-driven architecture and how front-end applications consume services
- Exposure to sales intelligence, licensing/royalties, enterprise operations, or similar business domains
- Experience working with offshore or distributed engineering teams across time zones
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