The MAI Monetization organization at Microsoft seeks a Senior Technical Program Manager to lead execution of Ads monetization programs. This role involves hands-on product development and delivery leadership from product intent through launch and post-launch measurement. Responsibilities include managing delivery plans, driving execution against revenue goals, bridging product and engineering teams, coordinating cross-functional dependencies, running A/B tests with Product and Data Science, ensuring operational excellence, managing communication and stakeholder alignment, and using AI tools to prototype technical solutions. Required qualifications include a Bachelor's degree with 4+ years in engineering, product/technical program management, data analysis, or product development, plus 2+ years managing cross-team projects. Preferred qualifications include 8+ years experience, advertising or ad-tech experience, experimentation expertise, finance partnership, ad-tech system knowledge, AI/ML system experience, large-scale distributed system delivery, and coding experience. The role is full-time, on-site in Redmond, Washington, with salary ranges from $119,800 to $234,700 annually depending on location.
What you'll do
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Own end-to-end delivery of Ads monetization programs from product intent through flighting, launch, and post-launch measurement with accountability for timelines, quality, and business outcomes
Build and maintain delivery plans, schedules, and operating rhythms to keep teams aligned and predictable
Drive execution against revenue goals and release commitments; proactively surface and close gaps
Bridge product intent and engineering execution; translate PRDs into execution plans and engineering requirements
Provide context for architecture and technical trade-off decisions across ad delivery, targeting/bidding, ranking, ad serving, and monetization surfaces
Identify and manage dependencies across Engineering, Product, UX, Data Science, MSA, PMM, Compliance, and Operations
Resolve trade-offs, drive conflict resolution, and manage information flow to unblock execution
Partner with Product and Data Science to run A/B tests, validate monetization hypotheses, measure revenue and user-experience impact, and drive prioritization
Define success indicators; track program health and launch/post-launch metrics; maintain dashboards and reporting
Drive delivery discipline through documentation rigor, readiness reviews, and consistent execution frameworks
Coordinate privacy, security, and compliance readiness for monetization launches; support budget/financial reporting
Communicate proactively and escalate risk early; facilitate alignment discussions and keep stakeholders updated
Build alignment among engineering and product leaders across Ads, Search, and partner teams
Use AI/coding tools to build lightweight prototypes and technical artifacts to validate assumptions and accelerate solution exploration
Requirements
Bachelor's Degree AND 4+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience
2+ years of experience managing cross-functional and/or cross-team projects
Preferred: Bachelor's Degree AND 8+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience
Preferred: 4+ years experience managing cross-functional and/or cross-team projects
Preferred: 2+ years experience in advertising, monetization, search, commerce, or marketplace/ad-tech systems
Demonstrated experimentation background — designing and interpreting A/B tests and using data to drive product decisions
Experience partnering with Finance/Business on revenue modeling and business-impact measurement
Working knowledge of ad-tech systems: real-time/programmatic auctions, bidding, ranking algorithms, click-through prediction, ad serving, and campaign platforms
Experience with AI/ML-powered systems (personalization, recommendation, or AI-driven monetization)
Experience delivering on large-scale distributed, real-time, or high-volume data systems
