[Hiring] Certified AI Infrastructure and Kubernetes Platform Architect @IT Search Corp

Role Description

We are seeking a highly skilled AI Infrastructure and Kubernetes Platform Architect with deep expertise in managing GPU-accelerated workloads on NVIDIA DGX systems. The ideal candidate will have hands-on experience with Kubernetes at the administrator, application developer, and security levels (CKA, CKAD, CKS), and will be responsible for designing, deploying, securing, and maintaining large-scale AI infrastructure powered by DGX BasePODs and SuperPODs. This role involves optimizing AI workloads, managing high-performance networking (InfiniBand), and ensuring operational excellence across NVIDIA AI systems and BlueField DPU environments.

Key Responsibilities

• Kubernetes and AI Platform Orchestration
  • Architect and maintain containerized AI/ML platforms using Kubernetes on DGX systems.
  • Integrate NVIDIA Base Command Manager with Kubernetes for workload scheduling and GPU resource optimization.
  • Design multi-tenant GPU resource partitioning strategies using MIG (Multi-Instance GPU) to maximize hardware utilization across concurrent AI workloads.
  • Implement and manage Helm charts, custom controllers, and GPU operators for scalable ML infrastructure.
• DGX Infrastructure Administration
  • Administer and optimize NVIDIA DGX BasePODs and SuperPODs.
  • Ensure optimal GPU, CPU, and storage performance across AI clusters.
  • Leverage DGX System Administration best practices for lifecycle management and updates.
  • Coordinate capacity planning for DGX cluster expansion including rack power, cooling, and storage integration with NVIDIA AI Enterprise software stack.
• High-Performance Networking & DPU
  • Deploy, monitor, and manage InfiniBand networks using Unified Fabric Manager (UFM).
  • Integrate BlueField DPUs for offloaded security, networking, and storage tasks.
  • Optimize end-to-end data pipelines from storage to GPUs.
• Security and Compliance
  • Apply best practices from the CKS certification to harden Kubernetes clusters and AI workloads.
  • Implement secure service mesh and microsegmentation with BlueField DPU integration.
  • Conduct regular audits, vulnerability scanning, and security policy enforcement.
• Automation & Monitoring
  • Automate deployment pipelines and infrastructure provisioning with IaC tools (Terraform, Ansible).
  • Monitor performance metrics using GPU telemetry, Prometheus/Grafana, and NVIDIA DCGM.
  • Troubleshoot and resolve complex system issues across hardware and software layers.
  • Implement MLOps workflows integrating KubeFlow Pipelines, NVIDIA Triton Inference Server, and model registry tooling to support end-to-end model training and production deployment.

Qualifications

• CKA, CKAD, CKS certifications – demonstrating full-stack Kubernetes expertise.
• Proven experience with NVIDIA DGX systems and AI workload orchestration.
• Hands-on expertise in InfiniBand networking, UFM, and BlueField DPU administration.
• Strong scripting and automation skills in Python, Bash, YAML.
• Familiarity with Base Command Manager, NVIDIA GPU Operator, and KubeFlow is a plus.
• Ability to work across teams to support ML researchers, DevOps engineers, and infrastructure teams.