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Hewlett Packard Enterprise Logo Hewlett Packard Enterprise · IT - Software Development

Product Manager - AI Data Center Infrastructure

India, Bangalore · Job Posted March 04, 2026
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Job Description

Product Manager - AI Data Center Infrastructure. We are seeking a Product Line Manager (PLM) for AI Data Center Infrastructure to define and deliver next-generation data center networking platforms for large-scale GPU clusters. This role is ideal for a visionary, hands-on leader who understands how AI workloads stress networks at scale and can translate that insight into clear product requirements and roadmaps.

Job Responsibility

  • AI Data Center & Fabric Architecture: Define product requirements for AI data center network architectures supporting thousands of GPUs
  • Develop requirements for low-latency Ethernet fabrics using Juniper QFX platforms and Apstra-based automation
  • Enable high-bandwidth GPU and NIC interconnects optimized for large-scale distributed training and inference workloads
  • GPU, NIC & Interconnect Strategy: Lead requirements definition for next-generation GPUs, NICs, and interconnect technologies, staying ahead of industry roadmaps
  • Drive alignment with NVIDIA and AMD ecosystems
  • Ensure interoperability across DAC, AEC, ACC, and optical transceivers between switches and NIC endpoints
  • Define scale-up paths using PCIe, NVLink, NVSwitch, ensuring GPU-to-GPU symmetry, consistency, and bandwidth determinism
  • Switching, Routing & Telemetry: Specify and optimize L2/L3 architectures, including EVPN-VXLAN, Class-E IPv4, and AI-optimized buffer tuning
  • Leverage hardware telemetry, streaming sensors, and analytics for proactive performance assurance
  • Drive automation using Python, Ansible, Apstra, Terraform, and related tools to enforce configuration consistency and compliance
  • Performance Optimization & Troubleshooting: Analyze GPU job performance to identify network hotspots, congestion, packet loss, and microbursts
  • Tune ECN, RDMA/ROCEv2, PFC, and traffic-engineering policies for AI workloads
  • Optimize server-to-switch interactions, including BIOS and firmware alignment, NIC queue and link-training parameters, Cable selection and management (AEC/ACC/optics)
  • Cross-Functional & Ecosystem Collaboration: Partner closely with AI platform teams, GPU system architects, data center operations, and strategic vendors (NVIDIA, AMD, Juniper)
  • Lead and participate in root-cause analysis for Link flaps and training failures, FEC and PCS errors, Thermal or power-related performance degradation
  • Drive lab validation, scale testing, and certification of new optics, NIC firmware, and switch software releases

Requirements

  • 5–10+ years of experience in data center networking, AI infrastructure, or HPC environments
  • Strong hands-on experience with Juniper QFX platforms and JunOS
  • Deep understanding of GPU architectures: NVIDIA: H100/H200, GB200/GB300, NVLink/NVSwitch AMD: MI300/MI400, Pollara NICs, Infinity Fabric
  • Proven expertise in scale-up GPU interconnects and scale-out Ethernet fabrics
  • Strong knowledge of RDMA/ROCEv2, ECN, PFC, and buffer management
  • Familiarity with distributed AI workloads, collective operations (NCCL, RCCL)
  • Hands-on troubleshooting experience with high-speed optics, AEC cables, link training, and NIC firmware
  • Proficiency in automation and scripting (Python, Ansible, Bash, Terraform)

Nice to have

  • Certification: JNCIE, CCIE, (NCP-AII), (NCA-AIIO), (NCP-AIO), (NCP-AIN)
  • Experience with Apstra or other intent-based networking platforms
  • Knowledge of 1.6T optics, 200G PAM4 SerDes, and CPO/LPO architectures
  • Experience supporting liquid-cooled GPU clusters and rack-level power/network design
  • Understanding of data center operations, observability, and SLAs for AI training and inference clusters

What we offer

  • Health & Wellbeing: comprehensive suite of benefits that supports physical, financial and emotional wellbeing
  • Personal & Professional Development: specific programs catered to helping you reach any career goals
  • Unconditional Inclusion: unconditionally inclusive in the way we work and celebrate individual uniqueness
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