Solution Designer

4 days ago

Guntur, Andhra Pradesh, India beBeeSolution Full time ₹ 1,75,00,000 - ₹ 2,15,00,000

Role Overview

We are seeking a seasoned infrastructure professional to design and implement cutting-edge platforms that drive enterprise-grade AI workloads forward.

Key Responsibilities:

  • Infrastructure Design
    • Design and build HPE Private Cloud AI and HPC solutions to support AI workloads
  • Collaboration and Delivery
    • Collaborate with cross-functional teams to deliver infrastructure projects
  • Technical Alignment
    • Align technical solutions with business goals
  • Staying Current
    • Stay up-to-date with industry trends and technologies in AI, HPC, and Kubernetes
  • Troubleshooting
    • Troubleshoot and resolve complex technical issues

Requirements

Technical Skills:

  • Container Orchestration
    • Proficiency in container orchestration platforms, especially Red Hat OpenShift, SUSE Rancher, and CNCF Kubernetes
  • GPU-Accelerated Workloads
    • Experience with GPU-accelerated workloads and tools like NVIDIA GPU Operator and DCGM
  • Kubernetes Integration
    • Proven ability to integrate Kubernetes with AI/ML workloads and GPU infrastructure in hybrid or private cloud environments
  • HPC Cluster Architecture
    • Experience architecting HPC clusters, including GPU/compute nodes and HPC storage technologies (e.g., Lustre, WEKA, Parallel Filesystems)
  • Networking Fundamentals
    • Understanding of high-speed networking (e.g., InfiniBand, Mellanox, RoCE)
  • Cluster Management Tools
    • Experience with HPC cluster management tools such as HPE Cluster Management (HPCM) or NVIDIA Base Command Manager
  • Workload Schedulers
    • Familiarity with HPC workload schedulers like Slurm or Altair PBS Pro
  • System Administration
    • Strong background in Linux system administration (RHEL / SLES /Ubuntu) and virtualization (KVM or OpenShift Virtualization)
  • Compute, Storage, and Networking
    • Primary focus on HPE servers and storage; experience with Dell, Lenovo, Supermicro, NVIDIA DGX/HGX platforms is acceptable
  • AI Enterprise Deployment
    • Solid understanding of compute, storage, and networking fundamentals in enterprise environments
  • DevOps/MLOps Practices
    • Experience deploying and supporting NVIDIA AI Enterprise and related AI/ML frameworks
  • Soft Skills
    • Project Delivery
      • Demonstrated success in infrastructure project delivery
    • Collaboration
      • Ability to collaborate with cross-functional teams
    • Trainability
      • Trainability clause: candidates with strong Kubernetes or HPC and AI/ML experience but limited infrastructure hardware exposure may be considered if they demonstrate trainability in server and platform environments

Preferred Qualifications

Desirable Experience

HPC experience is strongly preferred

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