Jobgether
Jobgether

Senior Technical Operations & Deployment Engineer (GPU Cloud Infrastructure)

engineeringfull-timeGermany
SALARY
Not listed
WORK TYPE
remote
JOB TYPE
full-time
INDUSTRY
general
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About the role

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.
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Senior Technical Operations & Deployment Engineer (GPU Cloud Infrastructure) at Jobgether — Remote