Job description
Senior Product Manager – GPU Products & AI Infrastructure
Why This Opportunity?
This is an opportunity to shape the future of AI and accelerated computing in the cloud. You will play a pivotal role in defining the GPU products, clusters, and services designed to support demanding AI, HPC, graphics, and enterprise workloads at a global scale. Working at the intersection of product strategy, AI infrastructure, cloud computing, and advanced GPU technology, you will partner with engineering and industry technology leaders to bring innovative, foundational products to market
What We're Looking For (Required & Elite Qualifications)
To land this role, you must possess a rare blend of deep hardware-level intelligence and hyperscale product management acumen. We are filtering for candidates who meet the following high-bar criteria:
Professional Experience:12+ years of relevant product management, technology, or engineering experience in massive-scale cloud or hardware ecosystems.
Target Domain Expertise:Direct, hands-on experience managing GPU cloud infrastructure or accelerated computing products.
AI & Accelerated Computing:Strong technical understanding of GPU architectures (e.g., NVIDIA, AMD), CUDA, and accelerated computing platforms.
Cluster Orchestration:Deep experience with AI/HPC workloads and GPU cluster orchestration(including resource management, fabric, interconnects like NVLink/InfiniBand, and large-scale GPU deployments).
Financial Mastery:Proven capability in developing complex business and financial frameworks for infrastructure, including pricing, TCO, or profitability models.
Advanced Infrastructure Literacy:Deep knowledge of AI workload patterns, enterprise security requirements, and hardware-level APIs related to GPU infrastructure.
Execution & Leadership:A strong customer-first mindset with a hyper-focus on automation, usability, and low-friction integration for data scientists. Exceptional ability to gain buy-in from highly technical engineering teams.
Education: Bachelor's degree in Computer Science, Engineering, or equivalent deeply technical practical experience
What You'll Do
GPU Strategy & Vision:Define the product strategy, vision, and roadmap for next-generation GPU instances, high-performance clusters, and cloud services.
Workload Architecture: Translate complex AI, HPC, graphics, and accelerated-computing workloads into rigid product specifications, performance requirements, and technical architectures.
Lifecycle & Investment:Guide the evolution of GPU infrastructure and make data-driven decisions around platform investments, resource management, and lifecycle management from concept to end-of-life.
Cloud Economics:Develop advanced business cases, financial models, pricing strategies, profitability analyses, and TCO models to aggressively support product investments.
Ecosystem Partnership:Partner directly with primary GPU technology and ecosystem providers to align roadmaps, integrations, and bleeding-edge technical requirements.
Go-To-Market Execution:Develop and execute comprehensive go-to-market strategies, including product messaging, positioning, launch plans, and customer engagement alongside sales and solutions engineering.
User Advocacy:Represent the direct needs of enterprise customers, engineers, and data scientists by identifying opportunities to improve automation, orchestration, monitoring, and usability.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.