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Senior Technical Operations & Deployment Engineer (GPU Cloud Infrastructure)

jobgether · Germany

RemoteExternal listingfull-timeabout 1 hour ago

About The Role

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 Germany.

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.

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