Senior Product Manager – GPU Products

What You’ll Do

• Define the product strategy, vision, and roadmap for GPU instances, clusters, and cloud services.
• Align product positioning, requirements, and priorities with customer needs, market trends, and business objectives.
• Manage the full product lifecycle, from initial planning and launch through ongoing optimization and eventual end-of-life.
• Develop business cases, financial models, pricing strategies, profitability analyses, and TCO models to support product investments and decisions.
• Develop and execute go-to-market strategies, including product messaging, positioning, launch plans, and customer engagement in partnership with marketing, sales, and solutions engineering.
• Partner with GPU technology and ecosystem providers to align roadmaps, integrations, and technical requirements.
• Translate AI, HPC, graphics, and other accelerated-computing workloads into product specifications, performance requirements, and technical architectures.
• Guide the evolution of GPU infrastructure and make data-driven decisions around platform investments and lifecycle management.
• Represent the needs of customers, engineers, and data scientists by identifying opportunities to improve usability, automation, monitoring, support, and maintenance processes.
• Build strong relationships with engineering teams and secure alignment around product goals, technical requirements, and future GPU capabilities.

What We’re Looking For

• 12+ years of relevant product management, technology, or engineering experience and a bachelor's degree in computer science, Engineering, or equivalent experience.
• Strong technical understanding of GPU architectures, CUDA, and accelerated computing platforms.
• Experience with GPU resource management and cluster orchestration for AI and high-performance computing workloads.
• Knowledge of cloud networking, GPU interconnects, infrastructure redundancy, and large-scale GPU deployments.
• Experience developing both technical and business models for GPU/cloud products, including pricing, profitability, and Total Cost of Ownership (TCO) analysis.
• Understanding of AI workload patterns, enterprise security requirements, and hardware-level APIs related to GPU infrastructure.
• A strong customer-first mindset, with a focus on automation, usability, and low-friction integration for GPU workloads.
• Proven ability to collaborate with highly technical engineering and data science teams and gain buy-in for new product initiatives.
• Strong communication, strategic thinking, and stakeholder management skills.
• Ability to balance complex technical requirements with customer needs and business objectives.