Sr Product Manager, Technical - AI Governance Control Products

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This role turns T-Mobile's AI governance processes into products employees can actually use. The governance bodies own the decisions — what gates a model release, when an exception is granted, how an incident escalates, what oversight requires. You own how each of those processes shows up for the people who use them, and the experience that results: a release calendar teams can plan against, an exception request that is clear about what is needed and when an answer comes, an incident intake anyone can raise, and oversight measures presented so leaders can act. You'll run these like any product — a roadmap, a backlog, and continuous iteration with the bodies and pillars as models, threats, and regulation change. Success looks like governance processes employees describe as clear and fast — decisions by the bodies, experience by you, cycle-time SLAs published and visible, proving that governance accelerates the work rather than slows it.

Productize the model release process for employees — the release calendar, what is changing and when, and how teams prepare — with release decisions staying with the governance bodies and Cybersecurity. Own the exception and waiver request experience — what a complete request looks like and status visibility through decision — with approval authority remaining with the owning pillar. Own the incident intake and communication experience — how anyone reports AI misbehavior and how status and lessons are shared — against the response process the bodies define. Present the oversight-effectiveness measures — override rates, review times, outlier approvers — to the Steering Committee in a form leaders can act on. Keep process cycle-time SLAs visible so governance provably does not slow the work; publish override rates, review times, and outlier approvers to the AI Steering Committee Partner with Legal, Cyber, SOX, and Privacy to ensure governance control products stay current as regulation, model risk, and AI policy evolve Collaborate with the AI Hub build engineer and platform teams to automate governance workflows — reducing manual steps in release gating, exception routing, and incident intake Manage product backlog, roadmap, and Agile ceremonies across governance control products Also responsible for other duties/projects as assigned by business management as needed Education and Work Experience Bachelor's Degree plus 7 years of related work experience OR Advanced degree with 5 years of related experience (Required) Acceptable areas of study include Computer Science, Engineering, IT or equivalent experience. (Required) 6+ years of technical product management or solution engineering experience, ideally in a platform, compliance, workflow automation, or governance context. (Required) 7+ years of relevant Product Management experience in an agile software product development environment. Advanced-level understanding of customer experience. (Required) Required Knowledge, Skills and Abilities Agile Methodology Backlog Management Customer Centricity Data Analysis Problem Solving Product Management Product Roadmap Stakeholder Management Strategic Alignment Compliance & Audit Process Knowledge SLA & Cycle-Time Measurement AI Governance & Risk Management Process Design & Automation Executive Reporting Preferred Knowledge, Skills and Abilities Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001, SOX) Experience with workflow automation or intake tooling platforms Knowledge of