HPE
Senior Product Manager
$126K–$290K
Spring, Texas, United States of America +2 · Manager · Full-time · Posted Oct 5, 2026
- Location
- Spring, Texas, United States of America
Ft. Collins, Colorado, United States of America
Andover, Massachusetts, United States of America - Experience
- 8+ years in HPC or AI/ML platform infrastructure and tools; 8+ years of product management in B2B SaaS or IaaS focused on HPC or AI/ML and data infrastructure.
- Education
- Bachelor's degree or equivalent in computer science, engineering, or related field of study; MBA or advanced degree in computer science or engineering preferred.
About the job
Leads strategy, roadmap, development, and lifecycle management for HPE Private Cloud AI data infrastructure products, working across technical and go-to-market teams to bring enterprise AI solutions to market.
What you'll do
- Define and execute product strategy and roadmaps for Private Cloud AI products or portfolios.
- Develop product value propositions, customer segments, business cases, and market requirements.
- Coordinate stakeholders and value-chain partners across product planning, development, launch, and management.
What they ask for
- 8+ years of work experience in HPC or AI/ML platform infrastructure and tools.
- 8+ years of product management experience in B2B SaaS or IaaS, focused on HPC or AI/ML and data infrastructure.
- Technical understanding of the HPC or AI/ML tooling and infrastructure industry.
- Bachelor's degree or equivalent in computer science, engineering, or a related field of study.
Nice to have
- MBA or advanced degree in computer science or engineering.
- Expertise in HPC or AI and ML hardware, ecosystem, and software.
Pay
USD 132,500 - 252,500 (base salary, Colorado); USD 143,000 - 273,000 (base salary, Massachusetts); USD 126,500 - 290,500 (base salary, Texas)
Tools
HPC, AI/ML, B2B SaaS, IaaS, Private Cloud AI, MRD/PRD
AI focus
Build and evolve private cloud data infrastructure and AI/ML platform products that support enterprise data scientists and ML engineers in building and operating ML workflows at scale.
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