About The Position

We are seeking a Sr. Product Manager to lead our physical infrastructure solutions for Enterprise AI deployments. This role will drive the strategy and execution of integrated solutions across racks, power distribution, UPS, thermal management, and remote management—designed to support GPU-accelerated computing and high-performance AI systems. The portfolio will focus on enterprise data center deployments of advanced platforms such as NVIDIA DGX Station, RTX Pro servers, and Grace Blackwell systems, delivering optimized solutions that combine compute, power, cooling, and management into a seamless customer experience. settings.

Requirements

  • Experience: 10+ years in product management, solutions management, or technical product leadership in data center, HPC, or AI infrastructure.
  • Domain Knowledge: Deep knowledge of UPS, PDUs, racks/containment, thermal management, and remote management.
  • AI Expertise: Familiarity with GPU-based AI platforms (NVIDIA DGX, RTX Pro, Grace Blackwell, or equivalent) and their requirements for power, cooling, and density management.
  • Leadership: Demonstrated ability to lead cross-functional teams, manage complex solution roadmaps, and deliver enterprise-ready offerings.
  • Skills: Excellent communication, customer engagement, and strategic planning abilities, with a proven record of influencing across technical and executive stakeholders.

Responsibilities

  • Define Strategy & Vision: Build and own the roadmap for enterprise-ready infrastructure solutions purpose-built for AI workloads.
  • Drive Solution Integration: Deliver validated, scalable rack and containment systems engineered for high-density GPU and AI server deployments.
  • Partner with Customers & Ecosystem: Work closely with enterprises, OEM partners, hyperscalers, and system integrators to capture requirements and deliver enterprise AI infrastructure that reduces deployment risk and accelerates time-to-value.
  • Own Full Product Lifecycle: Manage solution performance from concept through launch, balancing performance, cost, and scalability for enterprise environments.
  • Track Market & Competitive Trends: Anticipate future needs in AI model training, inference, and enterprise adoption—ensuring our solutions lead the market.
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