[Hiring] Linux Infrastructure Engineer @Uvation

Role Description

We are seeking a highly experienced Senior Linux Infrastructure Engineer with deep expertise in Linux administration, bare metal infrastructure, enterprise storage, and next-generation AI Factory / GPU infrastructure platforms. This role is focused on designing, deploying, operating, and troubleshooting large-scale Linux-based infrastructure that powers both traditional enterprise workloads and modern AI/ML environments. This is not a DevOps-focused role. We already have a dedicated DevOps team and are looking for an engineer with extensive hands-on experience in Bare Metal as a Service (BMaaS), GPU infrastructure, high-performance storage, data center operations, and enterprise Linux platforms.

The ideal candidate will have experience building and managing infrastructure from the hardware layer up, including servers, networking, storage, GPU clusters, and AI-ready platforms. They should be comfortable working with high-performance computing (HPC), AI Factory environments, and large-scale Linux deployments where performance, reliability, and operational excellence are critical.

Qualifications

• Expert-level Linux administration (Ubuntu required; Red Hat and SUSE preferred)
• Deep expertise in bare metal server deployment, architecture, provisioning, and lifecycle management
• Experience operating Bare Metal as a Service (BMaaS) platforms and large-scale infrastructure environments
• Strong understanding of server hardware, including BIOS/UEFI, RAID controllers, firmware management, iLO/iDRAC/IPMI, NICs and SmartNICs, HBA cards, hardware diagnostics and troubleshooting
• Experience designing, implementing, and supporting enterprise Linux infrastructure at scale
• Experience deploying and managing GPU-accelerated infrastructure for AI/ML workloads
• Understanding of NVIDIA GPU technologies including A100, H100, H200, B200, or equivalent GPU platforms
• Knowledge of AI Factory architecture and infrastructure requirements
• Experience supporting GPU clusters, AI training environments, and high-performance computing (HPC) workloads
• Strong networking knowledge: Bonding, VLANs, Routing, MTU optimization, DNS, DHCP
• Experience with high-performance data center networking: 100G/200G/400G Ethernet, RoCE, RDMA, Spine-Leaf architectures
• Experience with high availability, clustering, and disaster recovery
• Strong troubleshooting skills across Linux operating systems, hardware platforms, GPU infrastructure, networking, and enterprise storage
• Bash and Python scripting for automation and operational efficiency

Requirements

• Experience with high-performance AI storage platforms such as WEKA, VAST Data, Dell PowerScale, Pure Storage FlashBlade, NetApp
• Understanding of NVMe-over-Fabrics (NVMe-oF), RDMA, GPUDirect Storage, parallel file systems, AI data pipelines
• Strong hands-on experience with Ceph, including cluster architecture, MON, OSD, MDS, RBD, CephFS, RGW, capacity planning, performance tuning, failure recovery
• Familiarity with NVIDIA ecosystem technologies such as CUDA, NCCL, GPUDirect Storage, NVIDIA Fabric Manager, NVIDIA Base Command (preferred)
• Experience creating operational documentation, runbooks, and infrastructure standards

Benefits

• Opportunity to work in a cutting-edge AI/ML environment
• Collaborative and innovative team culture
• Professional development and growth opportunities

Ideal Candidate

Someone who has spent years designing, building, and operating enterprise Linux environments, large-scale bare metal infrastructure, storage platforms, and modern AI Factory environments. The ideal candidate understands how to deploy and manage GPU-enabled infrastructure, BMaaS platforms, enterprise storage, and high-performance networking while solving complex operating system, hardware, storage, and AI infrastructure challenges. DevOps experience is a plus, but deep Linux, infrastructure, storage, BMaaS, and AI Factory expertise is the primary requirement.