Product Manager II

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This role sits at the intersection of AI, silicon, and system fundamentals. You will define and drive fundamentals strategies for AI workloads, partner with engineering and silicon teams, and build tools and data pipelines that provide deep insights into AI features, model behaviors, and system impact.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Required Qualifications:

• Bachelor’s degree in Computer Science, Engineering,
  • OR related technical field.
    
    
• 3+ years of experience in product/program management or technical leadership roles.

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Excellent written and verbal communication skills.
  
  
• Solid analytical skills and experience working with telemetry, diagnostics, or profiling tools.
  
  
• Proven ability to lead cross-functional initiatives and influence without authority.
  
  
• Experience with AI/ML systems, fundamentals, or performance engineering.
  
  
• Experience with system-level performance, power, or silicon fundamentals.
  
  
• Passion for building inclusive, customer-obsessed products.

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• Cross-Functional Leadership: Collaborate with engineering, silicon, and platform teams to define fundamentals requirements, prioritize scenarios, and drive execution.

• Data-Driven Insights: Leverage telemetry, performance profiling, and diagnostics to identify gaps, validate improvements, and inform product decisions.
  
  
• Tooling and Automation: Partner with engineering to develop scalable fundamentals tools and dashboards that provide visibility into AI model performance, accuracy, and system impact.
  
  
• Customer-Centric Design: Ensure fundamentals efforts reflect real-world usage and customer scenarios, with a focus on quality, reliability, and inclusivity.
  
  
• Communication and Influence: Clearly articulate fundamentals goals, findings, and trade-offs to technical and non-technical stakeholders, including executives.
  
  
• Continuous Improvement: Drive a culture of learning and iteration, using data and experimentation to refine fundamentals processes and improve product fundamentals.