Senior Network Engineer

Raydian Cloud; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

Raydian Cloud in Kuala Lumpur is seeking an AI Cluster Network Engineer to design, deploy, and optimize high-performance networks for AI/GPU computing and GPUaaS environments. You will work with NVIDIA Spectrum-X, InfiniBand, RoCEv2, and related technologies to deliver multi-tenant, secure, and scalable cluster networks.

The role focuses on RDMA tuning, NCCL traffic patterns, automation, observability, and production support across the Asia-Pacific region.

Qualifications

• Bachelor-level degree in CS/IT/Electronics/Telecommunications or related field.
• Minimum 5 years in large-scale data center networks, deployment and troubleshooting.
• Minimum 3 years with InfiniBand, RoCEv2, and RDMA technologies.
• Experience supporting AI/GPU clusters, HPC, or large distributed systems.

Responsibilities

• Design and deploy AI cluster networks using NVIDIA Spectrum-X and InfiniBand.
• Build leaf-spine, multi-tenant GPUaaS networks with proper segmentation.
• Tune and optimize RDMA, NCCL traffic, congestion control and QoS.
• Troubleshoot switches, NICs, DPUs, and Linux networking stack.
• Collaborate with compute/storage teams; perform performance validation.
• Develop automation, monitoring, runbooks, and incident response workflows.
• Provide POCs, benchmarks, and support production deployments in APAC.

Skills

BGP/ECMP/VXLAN

QoS/high availability

RDMA/NICs/RoCEv2

AI/GPU cluster networking

NCCL & HPC networking

Networking troubleshooting

Education

Bachelor’s degree in CS/IT/Electronics/Telecommunications

Tools

NVIDIA Spectrum-X

NVIDIA ConnectX NICs

NVIDIA BlueField DPUs

InfiniBand hardware

Arista/Cisco/Juniper gear

tcpdump/ethtool

Job description

1. Key Responsibilities

1.1 AI Cluster Network Architecture Design & Deployment

• Design and deploy AI cluster network architectures based onNVIDIA Spectrum-X EthernetandNVIDIA Quantum InfiniBandtechnologies.
• BuildLeaf-Spine and Clos network architecturescovering GPU compute networks, storage networks, management networks, and cross-site connectivity.
• Develop standard reference architectures forsingle-tenant and multi-tenant GPUaaS environments, including network segmentation, routing domains, and business zones.
• Evaluate and select network hardware based on performance, cost, reliability, scalability, and security requirements.

1.2 RDMA, RoCEv2 & InfiniBand Operations and Optimization

• Configure, operate, troubleshoot, and optimizeRoCEv2 and InfiniBand lossless networks.
• Perform in-depth RDMA performance tuning for distributed AI/ML workloads, includingNCCL, MPI, and inter-GPU traffic.
• Manage and optimizecongestion control, ECN, PFC, QoS, and adaptive routing.
• Troubleshoot communication bottlenecks caused by switches, NICs, DPUs, optical transceivers, firmware, and the Linux networking stack.

1.3 Cluster Integration & Performance Validation

• Work closely with compute, storage, and data center teams to integrate and commission GPUs, NICs, DPUs, storage nodes, and related infrastructure.
• Conduct network and cluster performance testing using tools such asib_write_bw, iperf, NCCL test suites, and other benchmarking tools.
• Establish performance baselines covering latency, bandwidth, packet loss, CRC errors, and other critical network metrics.
• Support customerPOCs, benchmark testing, technical validation, and production deployment.

1.4 Multi-Tenant Network Services

• Implement tenant isolation usingVLAN, VRF, VXLAN/EVPN, and related data center networking technologies.
• Design and deploy customer connectivity solutions including dedicated circuits, cloud interconnects,IPsec/VPN, and other secure access services.
• Operate network services including firewalls, load balancers, DNS, DHCP, and out-of-band management.
• Develop standardized deployment and onboarding templates to improve tenant provisioning efficiency.

1.5 Automation, Monitoring & Operations

• Develop network automation frameworks usingPython/Go, Ansible, CI/CD, and Infrastructure as Code (IaC).
• ImplementZero-Touch Provisioning (ZTP), configuration validation, automated deployment, and version rollback capabilities.
• Build comprehensive telemetry and monitoring covering port status, optical power levels, congestion, RDMA metrics, and other critical infrastructure indicators.
• Develop and maintain operational runbooks, escalation procedures, incident response processes, andRoot Cause Analysis (RCA)templates.
• Support24×7 production operationsand participate in on-call and emergency incident response.

1.6 Project Delivery & Technical Documentation

• Participate in data center planning, including rack layout, network cabling, IP addressing, hardware BOMs, and infrastructure design.
• ProduceHigh-Level Design (HLD), Low-Level Design (LLD), Method of Procedure (MOP), test plans, test reports, and other technical documentation.
• Provide technical support for major production incidents and participate in project deployments across theAsia-Pacific region.
• Coordinate with data center operators, hardware vendors, customers, and internal technical teams to ensure successful project delivery.

2. Requirements

2.1 Essential Requirements

• Bachelor’s degree or above inComputer Science, Information Technology, Electronics, Telecommunications, or a related discipline.
• Minimum5 years of experiencein large-scale data center network design, deployment, and troubleshooting.
• Minimum3 years of hands-on experiencewithInfiniBand, RoCEv2, and RDMA.
• Proven experience supportingAI/GPU clusters, High-Performance Computing (HPC), or large-scale distributed computing environments.

2.2 Required Technical Skills

• Strong knowledge ofBGP, ECMP, VXLAN/EVPN, QoS, high availability, and modern data center networking technologies.
• Hands-on experience withNVIDIA/Mellanoxnetworking products, including:
• NVIDIA Spectrum switches
• NVIDIA ConnectX NICs
• NVIDIA BlueField DPUs
• Familiarity with networking equipment from major vendors such asArista, Cisco, and Juniper.
• Strong Linux networking troubleshooting skills using tools such astcpdump, ethtool, and related utilities.
• Experience with network monitoring and observability platforms such asPrometheus, Grafana, and ELK.

2.3 Preferred / Additional Qualifications

• Hands-on experience deployingNVIDIA DGX, HGX, GB-series AI systems, Spectrum-X, or Quantum InfiniBand.
• Knowledge ofNCCL, GPUDirect RDMA, and large-scale AI/ML workload traffic patterns, including MoE workloads.
• Familiarity withKubernetes networking, Slurm, parallel file systems, NVMe-oF, and related AI/HPC technologies.
• Experience withPython/Go, Ansible, CI/CD, and network automation.
• NVIDIA, Arista, or other relevant vendor certifications are an advantage.

3. Performance Indicators & Additional Requirements

3.1 Key Performance Indicators

• Deliver network projects on schedule with complete and accurate cabling, configuration, testing, and acceptance documentation.
• EnsureRDMA and NCCL performancemeets defined customer and production requirements.
• Respond rapidly to network incidents and accurately identify root causes, with complete RCA documentation and corrective action plans.
• Continuously improve network automation, operational efficiency, tenant security, and network isolation.

3.2 Additional Requirements

• Willingness to travel frequently acrossAsia-Pacificcountries.
• Able to support scheduled night-time maintenance, emergency troubleshooting, and on-call operations when required.
• Comfortable working in a fast-paced project environment with multiple stakeholders.
• Strong communication and coordination skills when working with data center operators, hardware vendors, enterprise customers, and internal engineering teams.

4. Job Summary

TheAI Cluster Network Engineeris a key technical role responsible for designing, deploying, optimizing, and operating high-performance networks forAI/GPU computing and GPUaaS environments.

The role is deeply focused on NVIDIA’s advanced networking technologies, includingSpectrum-X Ethernet, Quantum InfiniBand, RoCEv2, RDMA, and high-performance cluster networking. The successful candidate will combine strong traditional data center networking expertise with hands-on experience in AI/HPC networking and distributed workload optimization.

In addition to network architecture and performance tuning, the role coversmulti-tenant network isolation, automation, observability, production operations, customer POCs, and project deliveryacross the Asia-Pacific region.

This position is ideal for a senior network engineer who wants to specialize inAI infrastructure, GPU clusters, high-performance computing, and next-generation data center networking, with a strong focus on commercial, production-grade GPUaaS deployments.