Microsoft
Senior AI Hardware Product Manager
$120K–$261K
Redmond, WA +3 · On-site · Manager · Full-time · Posted Oct 8, 2026
- Location
- Redmond, WA
Mountain View, CA
Hillsboro, OR
Austin, TX - Experience
- 5+ years required; preferred: Bachelor's Degree and 8+ years in product/service/program management or software development, or equivalent experience. Also listed as preferred: 2+ years taking products to market; 4+ years improving product metrics; 4+ years disrupting a market; 2+ years working on AI systems; 3+ years technical product management; and 3+ years creating product roadmaps and driving execution.
- Education
- Bachelor's Degree or equivalent experience.
About the job
Defines and leads the development of next-generation AI hardware for Azure, from customer needs and product requirements through investment decisions and execution.
What you'll do
- Translate customer needs, market opportunities, and competitive gaps into product requirements and specifications.
- Drive investment decisions using competitive, financial, architectural, risk, schedule, and hardware strategy analysis.
- Lead end-to-end technical programs with architecture, engineering, business teams, and senior leadership.
What they ask for
- Bachelor's Degree and 5+ years of product/service/program management or software development experience, or equivalent experience.
- Ability to meet Microsoft, customer and/or government security screening requirements, including the Microsoft Cloud Background Check.
Nice to have
- 2+ years of experience working on AI systems as an architect or product manager.
- Technical product management experience in datacenter hardware systems and/or cloud infrastructure; familiarity with AI systems roadmaps and infrastructure challenges.
Pay
USD $119,800 - $234,700 per year (base salary); USD $160,200 - $261,000 per year (base salary)
Tools
AI Hardware, Azure, GPU Architecture, Scale Up and Scale out networking, Data Center Specifications, Model Architecture, System Reliability, Nviida, AMD, Microsoft
AI focus
Defines Azure AI hardware for training and inference on AI models; requires proficiency in AI workload requirements, technology landscape, and industry roadmaps.
Model-written summary · the original posting is authoritative