AI Infrastructure Engineers – Network Design, Deployment & Operations (NCP-AIN/AII/AIO Certified)

NCP-Certified Engineers

Apply now to be part of cutting-edge AI deployments and scalable data center innovation!

1. Network Design & Installation Engineer (NCP-AIN Certified)

Location: India REMOTE

Duration: Long Term Contract

Overview:

Network Design & Installation Engineer

Key Responsibilities:

• Design and implement scalable InfiniBand/Ethernet networks to support large-scale H100 GPU clusters.
• Configure Spectrum-X switches, BlueField DPUs, and Cumulus Linux-based environments.
• Integrate networking architecture with existing data center infrastructure.
• Perform on-site installations, including racking, cable management, and connectivity validation.
• Utilize tools such as UFM and IBDiagnet to run diagnostics and optimize network performance.
• Collaborate with infrastructure and operations teams to ensure seamless deployment and expansion.

Qualifications:

• NCP-AIN certification (required)

  or strong equivalent hands-on experience.
• In-depth knowledge of InfiniBand, RoCE v2, Spectrum switches, BlueField DPUs, and Cumulus Linux.
• Proven experience in designing and deploying high-performance or HPC network environments.
• Willingness to travel for on-site deployments and hands-on hardware installation.
• Experience with telemetry, diagnostics, and fabric tuning tools.

2. AI Infrastructure Deployment Engineer (NCP-AII Certified)

Location: India REMOTE

Duration: Long Term Contract

Overview:

AI Infrastructure Deployment Engineer

Key Responsibilities:

• Lead end-to-end deployment of AI racks, including servers, GPUs, switches, and interconnects.
• Validate bare-metal hardware, Spectrum-X switches, routers, and storage systems.
• Configure multi-tenant GPU environments using MIG, MPS, and virtualization tools.
• Deploy NVIDIA Base Command, DGX OS, and associated AI/ML software stacks.
• Integrate systems with Kubernetes, Helm, and other orchestration platforms.
• Implement monitoring and telemetry using DCGM, UFM, and performance benchmarking tools.

Qualifications:

• NCP-AII certification (required)

  or equivalent hands-on infrastructure experience.
• Expertise in GPU server configurations, MIG/MPS, Base Command, and virtualization (K8s, vSphere).
• Experience with BIOS/firmware updates, system burn-in, and power/cooling validation.
• Strong understanding of data center infrastructure and AI workload requirements.
• Experience integrating AI infrastructure with cloud-native tools and container environments.

3. AI Infrastructure Operations Engineer (NCP-AIO Certified)

Location: India REMOTE

Duration: Long Term Contract

Overview:

AI Infrastructure Operations Engineer

Key Responsibilities:

• Manage day-to-day operations of GPU clusters, networking fabric, and server infrastructure.
• Monitor and maintain the health of InfiniBand/Ethernet networks and DGX/H100 nodes.
• Apply firmware upgrades, OS patches, and handle infrastructure lifecycle management.
• Troubleshoot hardware, network, and container-level failures using telemetry tools like UFM and DCGM.
• Create and maintain operational runbooks, automate workflows, and improve incident response.
• Support infrastructure scaling, upgrades, and collaborate with deployment teams.

Qualifications:

• NCP-AIO certification (required)

  or comparable operational experience in large-scale AI environments.
• Strong troubleshooting skills across compute, network, and storage domains.
• Experience with monitoring and telemetry tools (Prometheus, Grafana, DCGM, UFM).
• Familiarity with log aggregation and alerting systems.
• Background in data center operations, capacity planning, and support automation.

How These Roles Collaborate

• NCP-AIN (Design & Install):

  Builds and installs the high-speed network fabric that powers AI workloads.

• NCP-AII (Deploy):

  Deploys and validates the full AI infrastructure stack, including hardware and software integration.

• NCP-AIO (Operate):

  Ensures continuous, reliable, and optimized operations of deployed AI environments.