Network Consulting Engineer – VXLAN & AI Data Center Networking

NETS-International Group


Date: 9 hours ago
City: Riyadh
Contract type: Contractor
Riyadh, Saudi Arabia

contractual

Company Description

NETS is a leading global Solutions Provider and Systems Integrator dedicated empowering the future through our integrated approach and commitment to delivering Innovative, Intelligent, and Integrated Solutions (NETS 3 I’s) Effectively, Efficiently, and Economically (NETS 3 E’s). Our service portfolio covers 3 verticals namely Infrastructure, Digital, and Managed Solutions, and NETS Services include Access Networks (Fixed and Wireless), Enterprise Data Networks, Cloud Solutions, Cyber Security, Automation, Resource Outsourcing, and Managed Services. NETS brings over 4 decades of proven domain expertise, service specialization, and industry leadership, delivering over 3,000+ successful projects. Our 1,000+ highly skilled & professional staff, collaboration with over 50 leading global technology partners, 100+ NETS OEM Partners, and NETS Reach, with offices in the UK, UAE, USA, Saudi Arabia, and Pakistan, has allowed us to be the preferred trusted partner to over 200 long-standing satisfied customers including fortune 500 companies across 25+ countries.

Job Description

Network Consulting Engineer – VXLAN & AI Data Center Networking

Role Overview

We are seeking a highly skilled Network Consulting Engineer (NCE) to design and implement next-generation VXLAN EVPN-based data center networks that support hypercomputing and AI infrastructure. This role is central to enabling the high-performance, low-latency environments required for multi-GPU clusters, distributed training pipelines, and scalable AI workloads.

The ideal candidate will bring deep expertise in VXLAN, BGP, EVPN, RoCEv2, and fabric-based networking, along with a solid understanding of the networking demands of large-scale AI and HPC environments.

Key Responsibilities

  • Design, deploy, and manage VXLAN EVPN-based fabric networks supporting AI and high-performance computing workloads.
  • Build scalable spine-leaf architectures using Cisco Nexus 9000 or Arista switches, ensuring efficient Layer 2/Layer 3 segmentation and workload mobility.
  • Optimize network performance for RoCEv2, GPUDirect, and low-latency traffic flows, ensuring maximum throughput and minimal jitter for GPU-accelerated clusters.
  • Configure underlay and overlay protocols including BGP, OSPF, IS-IS, and troubleshoot connectivity and control-plane issues.
  • Integrate data center fabric with virtualization platforms such as VMware NSX, KVM, and Hyper-V, as well as Kubernetes-based AI infrastructure.
  • Collaborate with compute, storage, and DevOps teams to ensure end-to-end performance across AI training, fine-tuning, inference, and ETL pipelines.
  • Drive network automation efforts using tools such as Python, Ansible, and Terraform, enabling Infrastructure-as-Code (IaC) for repeatable, scalable deployments.
  • Participate in performance tuning, benchmarking, and capacity planning for evolving AI workloads and future-proof infrastructure designs.

Requirements

Required Skills & Expertise:

  • Proven experience designing and operating VXLAN EVPN-based data center networks.
  • Strong knowledge of Cisco ACI, Nexus 9000, or Arista EOS platforms.
  • Expertise in data center routing and switching, including BGP, OSPF, IS-IS, multicast, and fabric path.
  • Deep understanding of AI-specific networking needs, including RoCEv2, DCB, PFC, and RDMA optimization.
  • Hands-on experience with automation and orchestration tools such as Python, Ansible, and Terraform.
  • Familiarity with GPU-accelerated workloads and distributed systems in AI/ML and HPC environments.

Preferred Qualifications & Certifications

  • CCNP or CCIE Data Center (highly preferred)
  • Cisco Certified Specialist – Enterprise Core or Data Center Core
  • Additional certifications in NVIDIA Networking (Cumulus/Spectrum) or Arista ACE are a plus
  • Experience with hybrid and multi-cloud networking for AI clusters is desirable

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