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

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

📋 Description

• Design, implement, manage, and resolve issues related to extensive Linux-based infrastructure tailored for enterprise workloads and AI/ML environments.

• Construct and oversee infrastructure from the ground up, encompassing servers, networking, storage, GPU clusters, and platforms optimized for AI.

• Deploy, provision, manage, and oversee the lifecycle of bare metal servers and Bare Metal as a Service (BMaaS) platforms.

• Implement and manage GPU-accelerated infrastructure, GPU clusters, and environments for AI training.

• Provide support for high-performance computing (HPC) workloads and AI Factory environments.

• Manage enterprise-level Linux storage, Ceph clusters, and high-performance storage solutions for AI.

• Design and troubleshoot data center networking with high bandwidth and low latency.

• Ensure the stability of mission-critical production environments through high availability, clustering, and disaster recovery strategies.

• Diagnose and resolve issues related to operating systems, hardware, GPU, networking, and storage.

• Automate operational processes using Bash and Python scripting.

• Develop operational documentation, runbooks, and standards for infrastructure.

• Collaborate with a dedicated DevOps team, with a focus on infrastructure rather than CI/CD or application delivery.

⛳️ Requirements

• Expert-level proficiency in Linux administration; experience with Ubuntu is essential, while knowledge of Red Hat and SUSE is preferred.

• In-depth experience in deploying, architecting, provisioning, and managing the lifecycle of bare metal servers.

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

• Comprehensive understanding of server hardware, including BIOS/UEFI, RAID controllers, firmware management, iLO/iDRAC/IPMI, NICs and SmartNICs, HBA cards, and hardware diagnostics.

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

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

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

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

• Understanding of AI Factory architecture, GPU clusters, AI training environments, and HPC workloads.

• Knowledge of GPU resource allocation and scheduling, multi-GPU systems, GPU networking, and the design of high-bandwidth, low-latency infrastructure.

• Familiarity with 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, including cluster architecture, MON, OSD, MDS, RBD, CephFS, RGW, capacity planning, performance tuning, and failure recovery.

• Experience with high-performance AI storage solutions such as 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 equivalent technologies.

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

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

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

• Proficiency 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, NVIDIA Base Command Manager, Slurm/HPC schedulers, observability platforms, DCIM tools, IPAM solutions, and exposure to AWS/Azure/hybrid cloud environments is a plus.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance plans.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.

• A collaborative and innovative work environment.