Infrastructure Specialist (AI Networking)

The Infrastructure Specialist (AI Networking) is responsible for designing, implementing, operating, and securing high-performance network infrastructure that supports the Client’s AI/ML, cloud, and digital operations workloads. The role works closely with the Client’s Digital Operations team and AI infrastructure teams to deliver low-latency, high-bandwidth network fabrics for GPU clusters, hybrid/multi-cloud connectivity, network automation, and Zero Trust security. The role is based on-site at the Client’s premises in Abu Dhabi.

Roles & Responsibilities:

Network Design & Architecture

• Design and implement high-bandwidth, low-latency network topologies to support AI/ML workloads and GPU clusters.
• Architect LAN, WAN, SD-WAN and data center fabrics optimized for distributed AI training and inference workloads.
• Evaluate and deploy spine-leaf architectures with RDMA over Converged Ethernet (RoCE) or InfiniBand for AI compute networks.

AI & Cloud Infrastructure Support

• Support hybrid and multi-cloud network connectivity (AWS, Azure, GCP) for AI pipeline integration.
• Configure and manage network segmentation, VLANs and QoS policies to prioritize AI/ML traffic flows.
• Work with AI infrastructure teams to optimize network throughput for model training, data ingestion and inference serving.

Operations & Monitoring

• Implement AI-driven network monitoring and anomaly detection tools to proactively identify and resolve issues.
• Maintain and troubleshoot firewalls, load balancers, routers and switches in AI production environments.
• Develop automation scripts and workflows using Python, Ansible or Terraform for network provisioning and configuration management.
• Own incident response for network-related outages affecting AI services, ensuring swift resolution and RCA documentation.

Security & Compliance

• Enforce network security policies aligned with cybersecurity and data governance standards.
• Implement Zero Trust Network Architecture (ZTNA) principles across AI and data platform environments.
• Conduct regular network vulnerability assessments and participate in security audits.

Operations, Documentation & Stakeholder Management

• Support day-to-day infrastructure operations, troubleshoot incidents and provide technical support to end-users.
• Maintain accurate infrastructure documentation, system records and configuration baselines.
• Collaborate with senior specialists, Client’s departments and external vendors on infrastructure projects, upgrades and migrations.
• Provide accurate and timely updates to the line manager and prepare periodic reports as per Client’s reporting standards.
• Adhere to Client’s governance, HSE policies, code of conduct and applicable compliance requirements.
• Stay informed of industry trends and emerging AI networking technologies to continuously enhance skills and service quality.

Qualification and Education Requirements

• Bachelor’s degree in information technology, Computer Science, Digital Operations or a related field.
• Certifications (Preferred): CCIE or equivalent (Cisco, Juniper, Arista); Cloud certifications (AWS Advanced Networking Specialty, Azure Network Engineer Associate); NVIDIA DGX Networking or AI infrastructure-specific credentials are a plus.

Minimum Experience / Skills Required

• 10+ years of solid experience in networking and security or a closely related field.
• Minimum 2 years supporting AI / GPU infrastructure projects.
• Routing & Switching: Cisco and Juniper.
• AI Networking: RDMA, RoCE, InfiniBand, NVIDIA Networking (preferred).
• Cloud Networking: AWS VPC, Azure VNet, GCP VPC, Direct Connect / ExpressRoute.
• Security: Cisco, Palo Alto, Aruba ClearPass and similar platforms.
• Automation: Python, Ansible, Terraform, Netmiko, NAPALM.
• Monitoring: NetFlow, SNMP, Grafana, Prometheus and AI-based monitoring platforms.
• SD-WAN and Software-Defined Networking (SDN) platforms.
• Telephony: MS Teams Direct Routing.
• Network load balancing and application security: F5.
• Wireless Network: Aruba.
• Strong analytical and problem-solving skills, with the ability to work in a fast-paced AI-driven environment.
• Excellent communication and stakeholder management skills.