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Senior Technical Program Manager

Microsoft
Redmond, USA
Full-time
Senior · 8+ years experience
Onsite
Discovered Yesterday

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Drive AI transformation initiatives from ambiguous opportunities through experimentation, implementation, adoption, and scale. Partner deeply with engineering teams, applying strong technical judgment to understand designs, tradeoffs, and emerging AI and agentic capabilities. Lead multiple complex initiatives in parallel, establishing priorities, managing dependencies and risks, and maintaining execution velocity. Translate business and operational needs into clear outcomes, success measures, plans, and ownership. Provide cross-functional leadership, creating clarity, driving decisions, and aligning teams in fast-moving and ambiguous environments. Drive measurable operational impact through clear business metrics, evaluation, telemetry, and feedback loops that inform iteration and scaling decisions. Build trusted partnerships across Frontier and identify reusable patterns and approaches that enable successful transformations to scale. Ensure security, privacy, Responsible AI, and compliance requirements are incorporated throughout program execution. Bachelor's Degree AND 4+ years experience in engineering, product/technical program management, data analysis, or product development 2+ years of experience managing cross-functional and/or cross-team projects. Bachelor's Degree AND 8+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience. 6+ years of experience managing cross-functional and/or cross-team projects. 1+ year(s) of experience reading and/or writing code (e.g., sample documentation, product demos). Experience partnering with engineering teams to evaluate AI or agentic solutions and deliver them into production, incorporating security, privacy, Responsible AI, and compliance requirements. Experience leading multiple technical initiatives in parallel, translating ambiguous business needs into delivery plans, managing dependencies and risks, and driving solutions from experimentation through deployment and adoption with measurable operational outcomes.

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