Principal Product Manager

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Product Management

The Principal Product Manager will lead the strategy, design, development, and operation of Windows Supportability Intelligence dashboards, data pipelines, and AI agents. The role focuses on identifying Windows components that generate escalations, surfacing actionable recommendations, and alerting engineering leadership through AI-powered analysis of product telemetry and case patterns. The goal is to improve product quality and customer satisfaction by detecting and resolving issues faster.

What you'd actually do

  1. Deliver product insights on emerging errors and customer support patterns, with anomaly detection for proactive engagement before issues become widespread.
  2. Leverage AI, product telemetry, and agentic analysis of frontline case patterns to automatically detect supportability gaps, recurring product bugs, and inefficiencies in escalation processes that are invisible through conventional reports.
  3. Partner directly with Windows component owners, Data Science teams, and Customer Support to define metrics that measure Windows ability to detect, diagnose, and repair malfunctions with minimal friction to users and support engineers.
  4. Establish and drive a Supportability governance framework ensuring new Windows features ship with required diagnostics, clear troubleshooting paths, and readiness for rapid incident response.

Skills

Required

  • Bachelor's Degree AND 8+ years experience in product/service/project/program management or software development
  • Ability to meet Microsoft, customer and/or government security screening requirements

Nice to have

  • Proven experience driving the creation of complex software solutions at scale across organizational boundaries, aligning engineering, and partner teams to deliver measurable outcomes.
  • Proven experience building or owning data platforms, analytics systems, product health dashboards, or quality metrics at enterprise scale.
  • Demonstrated expertise with AI/ML technologies including LLMs, anomaly detection, or intelligent automation applied to operational or product data.
  • Experience with Windows telemetry, diagnostics, or servicing systems.
  • Familiarity with support ecosystems including escalation workflows, incident management platforms, and CRM systems.
  • Experience defining and driving cross-organizational governance frameworks or quality gates in large engineering organizations.
  • Proficiency with data analysis tools and languages to query, visualize, and derive insights from large-scale operational data.

What the JD emphasized

  • AI agents
  • agentic analysis

Other signals

  • AI-powered analysis
  • AI agents
  • anomaly detection
  • product telemetry
  • customer support patterns