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Linux Infrastructure Engineer (Bare Metal, Storage & AI Factory Infrastructure)

uvationβ€’Indiaβ€’πŸŒ Remote
Contract7-15
πŸ‘οΈ 0 viewsβ€’πŸ“ 0 applicationsβ€’Posted 9/8/2026β€’Expires 11/7/2026
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Job Description

Job Overview 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.

Key Responsibilities

& Required Skills Linux & Bare Metal Infrastructure 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 AI Factory & GPU Infrastructure 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 NVIDIA DGX and OEM GPU servers

Required Skills

UbuntuRed Hat LinuxSUSE LinuxBare Metal as a Service (BMaaS)BIOS/UEFIRAID controllersFirmware managementiLOiDRACIPMINICsSmartNICsHBA cardsHardware diagnosticsNVIDIA A100NVIDIA H100NVIDIA H200NVIDIA B200NVIDIA DGXGPU clustersEnterprise storageAI Factory environmentsLarge-scale Linux deploymentsOEM GPU servers

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