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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Technical Operations & Deployment Engineer (GPU Cloud Infrastructure - **Company:** Nvidia - **Location:** Spain (Remote available) - **Contract:** Temporary contract - **Skills:** Board Bringup, Artificial Intelligence, Bash Shell, Border Gateway Protocol, BIOS, Ubuntu (Operating System), Cloud Computing, Apache CloudStack, Nvidia CUDA, Computer Maintenance, Network Congestion, Data Centers, Linux, RAID, Distributed Data Store, Network Interface Controllers, Firmware, Hardware Interface Design, Monitoring of Systems, Python (Programming Language), Kernel-Based Virtual Machine, Linux System Administration, Routing, PCI Express, Quick EMUlator (QEMU), Remote Direct Memory Access, Ansible, Prometheus, Virtual Local Area Networks, Virtualization Technology, Weka, Zabbix, AI Infrastructure, Private Cloud Environment, Network Routers, Graphics Processing Unit (GPU), High Performance Computing, Performance Testing, Grafana, Hardware Testing, Firewalls (Computer Science), Kubernetes, Bare Metal, Hardware Infrastructure, Terraform, Network Server, Docker, Nvme - **Published:** August 29, 2026 - **Apply:** https://www.jobleads.com/es/job/e9960ba323064763363a66209858b6d91 ## About the Role * 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. ## 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 Spain. This is ahighly hands-oninfrastructure role focusedon deploying, commissioning, and operating GPUcloud environments acrossregional and coredatacenters. You will turnvalidated architecturesand bills ofmaterials into production-ready infrastructure spanninghardware, networking, storage, Linux, andplatform software. The role sitsat the intersectionof datacenter operations, GPU infrastructure, networkengineering, and cloudplatform operations. You will workwith high-densityNVIDIA GPU systems, advanced networking,storage platforms, Kubernetes, virtualization, and observabilitytooling. As a practicaltechnical escalation point, you will troubleshootcomplex issues acrossphysical and softwarelayers and driveincidents through resolution. You willalso help establishdeployment standards, validationprocedures, documentation, and operational practicesfor a rapidlyevolving AI infrastructureenvironment. The role offersbroad technical ownershipinan international, fast-moving setting wherehands-on executionand operational excellenceare essential., * 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. ## Related Videos - [Your Next AI Needs 10,000 GPUs. 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