Technical Product Manager, AI Platform – Remote (Needs to work in EST)
Duration:12+ Months
Rate: DOE
AI Transformation organization is building the company's enterprise AI capability on a vendor-agnostic, capability-based reference architecture: a governed enterprise MCP gateway, an Azure AI foundation, and a portfolio of production AI use cases anchored to business outcomes. You'll join the AI Architecture & Engineering team as one of its three founding members, shaping how a global enterprise adopts AI from the ground up.
The role
You'll run the AI capability roadmap day to day: the intake process for proposed AI tools and builds, the backlog and sequencing that turn business priorities into delivered engineering work, and the metrics that show the platform's value. This is a technical seat with real decision rights on sequencing and acceptance — your internal customers are business functions, transformation workstreams, and the delivery teams consuming the platform, and you'll hold your own in design reviews.
What you'll do
• Own the roadmap backlog: sequencing against business-value anchors and acceptance criteria for every use case
• Run the portfolio intake process end-to-end, coordinating technical assessment with the Enterprise AI Architect and keeping decisions documented
• Treat the platform as a product: onboard internal consumers and own adoption, usage, and cost metrics, building your own queries and dashboards where needed
• Run vendor proofs-of-concept as structured product evaluations: timelines, gate criteria, decision memos
• Partner with the AI Product Owner to convert prioritized business demand into scoped, sequenced engineering work
• Produce grounded, verifiable program metrics for executive reporting
Your first 90 days
• Have the intake process live and used for every new request
• See the roadmap backlog governing sprint commitments
• Deliver the first adoption, usage, and cost metrics into value reporting
Required qualifications
• 5–8+ years as a technical product manager or platform product manager in a platform, API, or infrastructure organization
• Technical literacy that survives a design review: APIs, identity, integration patterns, and enough LLM-systems fluency to write honest acceptance criteria
• Hands-on enough to self-serve: you can query data, build a dashboard, and prototype against an AI API to test what you're asking engineering to build
• A track record running intake or prioritization processes with genuine decision rights among competing senior stakeholders
•Experience building metrics programs: instrumentation requirements, adoption and cost reporting
•Executive-grade writing — decision memos, gate reviews, metrics narratives — with samples available on request
•AI assistants in your daily toolkit — we work with Claude and Microsoft Copilot for analysis, drafting, and program operations, and expect the same fluency from you
Preferred qualifications
• AI/ML platform product experience
• Enterprise transformation program exposure, including work alongside external consulting partners
• Familiarity with value-realization or benefits-tracking frameworks
• Working fluency with Azure DevOps or Jira at the workflow-design level
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