Senior Technical Operations & Deployment Engineer (GPU Cloud Infrastructure)

Jobgether; Ireland; On-site; EUR 90,000 - 120,000; Full time

Job summary

Jobgether, on behalf of our partner in Ireland, seeks a Senior Technical Operations & Deployment Engineer (GPU Cloud Infrastructure). You will deploy, commission, and run GPU cloud environments, spanning hardware, networking, Linux, and platform software.

You will work with high-density NVIDIA GPU systems, Kubernetes, virtualization, and observability tools, troubleshoot complex issues, and help establish deployment standards and runbooks for a rapidly evolving AI infra.

Qualifications

• Hands-on datacenter deployment and maintenance experience.
• Bringing GPU servers from bare metal through validation to production readiness.
• Experience with NVIDIA GPUs, drivers, and high-density compute environments.
• Familiarity with NVL72 rack-scale architectures and RoCE/RDMA.
• Strong Linux troubleshooting across kernels and drivers.
• Knowledge of virtualization and containerization (KVM, Docker, Kubernetes).

Responsibilities

• Coordinate datacenter deployments with providers, integrators, and internal teams.
• Support rack-and-stack for GPU/CPU servers, storage, switches, and PDUs.
• Validate cabling, optics, and connectivity across networks and storage.
• Commission GPU servers, storage nodes, and platform infrastructure.
• Perform burn-in, stress, and acceptance testing before production handover.
• Validate telemetry and monitoring across hosts and networking gear.

Skills

Datacenter deployment

GPU infrastructure

Linux troubleshooting

Kubernetes

Networking

Observability

Terraform

Ansible

Tools

Terraform

Ansible

Docker

KVM/QEMU

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Technical Operations & Deployment Engineer (GPU Cloud Infrastructure) based in Ireland.

This is a highly hands-on infrastructure role focused on deploying, commissioning, and operating GPU cloud environments across regional and core datacenters.
You will turn validated architectures and bills of materials into production-ready infrastructure spanning hardware, networking, storage, Linux, and platform software.
The role sits at the intersection of datacenter operations, GPU infrastructure, network engineering, and cloud platform operations.
You will work with high-density NVIDIA GPU systems, advanced networking, storage platforms, Kubernetes, virtualization, and observability tooling.
As a practical technical escalation point, you will troubleshoot complex issues across physical and software layers and drive incidents through resolution.
You will also help establish deployment standards, validation procedures, documentation, and operational practices for a rapidly evolving AI infrastructure environment.
The role offers broad technical ownership in an international, fast-moving setting where hands-on execution and operational excellence are essential.

Accountabilities

• Datacenter deployment: Coordinate deployments with datacenter providers, integrators, logistics teams, vendors, and internal engineering; validate rack layouts, power, cooling, airflow, cabling, labeling, and physical readiness.
• Rack and infrastructure commissioning: Support rack-and-stack activities for GPU and CPU servers, storage, switches, routers, firewalls, PDUs, serial/OOB systems, and supporting infrastructure.
• Cabling and connectivity: Validate fiber and copper cabling, optics, transceivers, breakout cables, port mappings, link speeds, redundancy, and management, storage, north-south, and east-west connectivity.
• Hardware bring-up: Commission GPU servers, storage nodes, and platform infrastructure while validating BIOS, BMC, firmware, NICs, DPUs, GPUs, NVMe, RAID/HBA, PCIe topology, NUMA, thermals, power, and hardware health.
• Hardware validation: Execute burn-in, stress, network, storage, and acceptance testing before production handover; troubleshoot issues involving GPUs, DPUs, NICs, optics, memory, disks, firmware, and BIOS.
• Network deployment support: Work with network engineering to validate switch configurations, routing, VLAN/VRF segmentation, BGP, ECMP, EVPN/VXLAN, OVS/OVN, VyOS, firewalls, WAF infrastructure, and customer connectivity.
• AI networking: Support validation of RoCE/RDMA fabrics for distributed AI workloads and troubleshoot issues such as link flaps, MTU mismatches, route errors, packet loss, PFC/ECN problems, and congestion.
• Platform installation: Install and validate Ubuntu/Linux environments, NVIDIA drivers, CUDA, OFED or inbox drivers, Docker/containerd, KVM/QEMU, platform agents, and GPU infrastructure components.
• Cloud and Kubernetes environments: Support CloudStack, Kubernetes, KubeVirt, GPU Operator, CSI/CNI integrations, GPU passthrough, SR-IOV, BlueField DPUs, VM networking, and container networking.
• Storage integration: Support integration and validation of StorPool, Weka, local NVMe, and other supported storage platforms.
• Operational readiness: Execute acceptance testing, produce deployment readiness reports, maintain runbooks, and ensure infrastructure is fully operational before customer or production handover.
• Day-2 operations: Perform controlled firmware, OS, driver, BIOS, switch, and hardware maintenance while supporting production incidents and infrastructure escalations.
• Incident management: Investigate operational failures, perform root-cause analysis, distinguish temporary workarounds from permanent fixes, and work with engineering to eliminate recurring issues.
• Observability: Validate telemetry and monitoring across hosts, GPUs, DPUs, switches, storage, and platform components using tools such as Zabbix, Prometheus, Grafana, Loki, DCGM/NVML, and NVIDIA NetQ or equivalents.
• Performance validation: Establish baselines for GPU, network, storage, and host performance and support benchmarking and infrastructure validation.
• Documentation: Maintain accurate as-built records covering rack elevations, cable maps, port mappings, serial numbers, asset records, IP allocations, changes, and operational procedures.
• Cross-functional coordination: Partner with infrastructure, networking, storage, platform, fleet automation, observability, product engineering, sales engineering, and service delivery teams.
• Vendor management: Coordinate with datacenter providers, system integrators, server and storage vendors, NVIDIA, and networking suppliers to resolve deployment and infrastructure issues.
• Continuous improvement: Feed field experience back into reference architectures, BOMs, rack designs, cabling standards, deployment playbooks, validation processes, and automation.

Requirements

• Datacenter infrastructure: Strong hands-on experience deploying and maintaining datacenter infrastructure, ideally within GPU, HPC, AI cloud, private cloud, or high-density compute environments.
• Bare-metal deployment: Proven ability to bring servers from physical installation and bare metal through validation and production readiness.
• GPU infrastructure: Experience with NVIDIA GPU servers, drivers, firmware, PCIe topology, hardware validation, and high-performance compute environments.
• Next-generation AI infrastructure: Familiarity with NVL72-style rack-scale architectures, NVLink/NVSwitch domains, in-rack networking, high-density power delivery, and OEM/NVIDIA validation requirements.
• Datacenter readiness: Ability to assess power density, cooling, rack dimensions, floor loading, containment, serviceability, maintenance access, and other physical requirements for AI infrastructure.
• Linux: Strong Linux troubleshooting capabilities and experience managing operating systems, kernels, drivers, and hardware interfaces.
• Networking: Practical knowledge of VLANs, VRFs, BGP, ECMP, OVS/OVN, routing, OOB management, and high-speed datacenter connectivity.
• GPU networking: Familiarity with NVIDIA/Mellanox networking, RoCE/RDMA, SR-IOV, BlueField DPUs, and high-performance east-west infrastructure.
• Virtualization and containers: Experience with KVM/QEMU, VFIO, PCI passthrough, Docker/containerd, Kubernetes, and/or KubeVirt.
• Storage: Experience integrating or troubleshooting local NVMe, storage nodes, and enterprise or distributed storage platforms.
• Automation: Familiarity with Terraform, Ansible, Bash, and/or Python for deployment, validation, configuration, or operational automation.
• Observability: Experience with infrastructure monitoring, telemetry, logs, metrics, health checks, and performance dashboards.
• Documentation: Strong attention to detail and discipline in producing accurate as-built documentation, runbooks, validation records, and handover materials.
• Troubleshooting: Strong systems-thinking ability across physical infrastructure, hardware, firmware, networking, Linux, storage, and platform layers.
• Operational mindset: Comfortable supporting production environments, deployment windows, operational escalations, and customer-impacting incidents.
• Communication: Able to clearly explain technical issues, risks, workarounds, and permanent solutions to engineering teams, vendors, and leadership.
• Personal qualities: Highly practical, detail-oriented, calm under pressure, autonomous, and comfortable working both inside datacenters and remotely with smart-hands teams.

Benefits

• Attractive compensation package reflecting your expertise, experience, transferable skills, and market conditions.
• Full-time or contract engagement, depending on the agreed arrangement.
• Europe-based remote working environment with flexibility.
• Opportunity to work on cutting-edge GPU cloud and AI infrastructure at significant scale.
• Hands-on exposure to NVIDIA GPU platforms, high-density datacenter environments, RoCE/RDMA networking, Kubernetes, virtualization, storage, and advanced observability.
• Broad cross-functional scope spanning hardware, datacenter operations, networking, storage, Linux, and cloud platforms.
• High-impact role within a fast-growing international scale-up.
• Strong opportunities for technical growth and career development as the infrastructure platform expands.
• Friendly, diverse, flexible, and international working environment.
• Inclusive workplace committed to equal opportunity and respect for all qualified candidates.