Linux Infrastructure Engineer – Bare Metal, Storage, AI Factory Infrastructure

atUvationRemote

Poland Full-time Infrastructure EngineerMid-levelSenior

Posted Aug 28

This is a fully remote position, open to applicants in Poland.

📋 Description

• Design, implement, operate, and troubleshoot extensive Linux-based infrastructure.

• Support both traditional enterprise workloads and contemporary AI/ML environments.

• Construct and oversee infrastructure from the hardware level upwards, which includes servers, networking, storage, GPU clusters, and AI-ready platforms.

• Deploy and manage GPU-accelerated infrastructure tailored for AI/ML workloads.

• Provide support for GPU clusters, AI training environments, and high-performance computing (HPC) tasks.

• Manage Bare Metal as a Service (BMaaS) platforms and expansive infrastructure settings.

• Design, implement, and maintain enterprise Linux infrastructure on a large scale.

• Administer and enhance enterprise storage systems and high-performance AI storage platforms.

• Oversee Ceph cluster architecture, including capacity planning, performance tuning, and failure recovery.

• Design and troubleshoot high-performance data center networking, along with Layer 2/Layer 3 infrastructure.

• Ensure support for high availability, clustering, disaster recovery, and mission-critical production environments.

• Conduct troubleshooting across Linux operating systems, hardware, GPU infrastructure, networking, and storage components.

• Utilize Bash and Python for automation and improving operational efficiency.

• Develop operational documentation, runbooks, and infrastructure standards.

⛳️ Requirements

• Expert-level Linux administration is required; proficiency in Ubuntu is essential, with Red Hat and SUSE being preferred.

• Extensive knowledge in bare metal server deployment, architecture, provisioning, and lifecycle management.

• Experience in operating Bare Metal as a Service (BMaaS) platforms and large-scale infrastructure environments.

• Strong comprehension of server hardware, encompassing BIOS/UEFI, RAID controllers, firmware management, iLO/iDRAC/IPMI, NICs and SmartNICs, HBA cards, and hardware diagnostics.

• Proven experience in designing, implementing, and supporting enterprise Linux infrastructure at scale.

• Familiarity with deploying and managing GPU-accelerated infrastructure for AI/ML workloads.

• Understanding of NVIDIA GPU technologies, such as A100, H100, H200, B200, or similar platforms.

• Proficiency with NVIDIA DGX and OEM GPU servers, including GPU provisioning, lifecycle management, monitoring, and performance optimization.

• Knowledge of AI Factory architecture and its infrastructure requirements.

• Experience providing support for GPU clusters, AI training environments, and HPC workloads.

• Familiarity with GPU resource allocation and scheduling, multi-GPU systems, GPU networking, and high-bandwidth, low-latency infrastructure design.

• Understanding of CUDA, NCCL, GPUDirect Storage, NVIDIA Fabric Manager, and NVIDIA Base Command.

• Advanced skills in Linux storage administration, including LVM, XFS, EXT4, NFS, iSCSI, Fibre Channel, SAN, and Multipath I/O.

• Significant hands-on experience with Ceph, covering MON, OSD, MDS, RBD, CephFS, RGW, capacity planning, performance tuning, and failure recovery.

• Familiarity with high-performance AI storage solutions like WEKA, VAST Data, Dell PowerScale, Pure Storage FlashBlade, and NetApp.

• Understanding of NVMe-over-Fabrics (NVMe-oF), RDMA, GPUDirect Storage, parallel file systems, and AI data pipelines.

• Strong networking expertise, including bonding, VLANs, routing, MTU optimization, DNS, and DHCP.

• Experience with 100G/200G/400G Ethernet, RoCE, RDMA, and Spine-Leaf architectures.

• Familiarity with NVIDIA Spectrum-X, Mellanox/NVIDIA ConnectX adapters, or similar technologies.

• Solid understanding of Layer 2 and Layer 3 infrastructure design and troubleshooting.

• Experience with high availability, clustering, and disaster recovery mechanisms.

• Strong troubleshooting capabilities across Linux operating systems, hardware platforms, GPU infrastructure, networking, and enterprise storage.

• Proficient in Bash and Python scripting for automation and operational efficiency.

• Experience in creating operational documentation, runbooks, and infrastructure standards.

• Familiarity with Kubernetes infrastructure, virtualization platforms, Ansible, Slurm/HPC schedulers, observability platforms, DCIM tools, IPAM solutions, and AWS/Azure or hybrid cloud is advantageous.

• Note: This role does not focus on DevOps; experience with CI/CD, Terraform, GitOps, application delivery, cloud-only administration, or software development is not required.