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

Job not on LinkedIn

🔥 23 minutes ago

🎰 Nevada – Remote

🎰 Nevada – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

👷 Infrastructure Engineer

👻 Ghost score 25%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Uvation

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

🏥 Healthcare

🤖 Artificial Intelligence

Consulting • Healthcare • Artificial Intelligence

Uvation is a comprehensive technology services company providing innovative solutions across the IT infrastructure space. They specialize in artificial intelligence and cutting-edge cybersecurity solutions, offering products powered by Dell and Nvidia AI. Uvation delivers various managed services, including IT operations, security operations, and network operations, optimizing performance and enhancing security for businesses. Their services extend into public clouds with partnerships involving major platforms like Oracle Cloud, Google Cloud, and Amazon AWS. Uvation also operates a marketplace offering competitive pricing on a wide range of hardware and software products and provides a rewards program to incentivize customer engagement.

📋 Description

• Design, deploy, operate, and troubleshoot large-scale Linux-based infrastructure for enterprise and AI/ML workloads • Build and manage infrastructure from the hardware layer up, including servers, networking, storage, GPU clusters, and AI-ready platforms • Deploy and manage GPU-accelerated infrastructure, GPU clusters, AI training environments, and HPC workloads • Provision and lifecycle-manage bare metal servers, BMaaS platforms, GPU systems, and enterprise infrastructure • Design, implement, and support enterprise Linux infrastructure at scale • Administer and optimize enterprise storage, Ceph clusters, high-performance AI storage, parallel file systems, and AI data pipelines • Design and troubleshoot high-performance data center networks and Layer 2/Layer 3 infrastructure • Monitor and optimize GPU and infrastructure performance • Support mission-critical production environments with high availability, clustering, and disaster recovery • Troubleshoot Linux operating systems, hardware, GPU infrastructure, networking, and storage • Automate operational tasks using Bash and Python • Create and maintain operational documentation, SOPs, runbooks, and infrastructure standards • Manage incidents, problems, capacity, business continuity, and disaster recovery planning for AI workloads • Identify and mitigate risks proactively to avoid business impact • Collaborate with the existing DevOps team while focusing on infrastructure engineering rather than CI/CD or application delivery

🎯 Requirements

• Expert-level Linux administration; Ubuntu required, with 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, and hardware diagnostics • 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 platforms • Experience with NVIDIA DGX and OEM GPU servers, GPU provisioning, lifecycle management, monitoring, and performance optimization • Knowledge of AI Factory architecture and infrastructure requirements • Experience supporting GPU clusters, AI training environments, and HPC workloads • Understanding of GPU resource allocation and scheduling, multi-GPU systems, GPU networking, and high-bandwidth, low-latency infrastructure design • Familiarity with CUDA, NCCL, GPUDirect Storage, NVIDIA Fabric Manager, and preferably NVIDIA Base Command • Advanced Linux storage administration: LVM, XFS, EXT4, NFS, iSCSI, Fibre Channel SAN, and Multipath I/O • Strong hands-on Ceph experience, including cluster architecture, MON, OSD, MDS, RBD, CephFS, RGW, capacity planning, performance tuning, and failure recovery • Experience with high-performance AI storage platforms such as WEKA, VAST Data, Dell PowerScale, Pure Storage FlashBlade, and NetApp • Understanding of NVMe-over-Fabrics, RDMA, GPUDirect Storage, parallel file systems, and AI data pipelines • Strong networking knowledge: bonding, VLANs, routing, MTU optimization, DNS, and DHCP • Experience with 100G/200G/400G Ethernet, RoCE, RDMA, spine-leaf architectures, NVIDIA Spectrum-X, Mellanox/NVIDIA ConnectX adapters, or equivalent technologies • Strong understanding of Layer 2 and Layer 3 infrastructure design and troubleshooting • Experience with high availability, clustering, and disaster recovery • Strong troubleshooting across Linux operating systems, hardware platforms, GPU infrastructure, networking, and enterprise storage • Bash and Python scripting • Experience creating operational documentation, runbooks, and infrastructure standards • Understanding of AI infrastructure design, reference architectures, and AI cloud integration • Experience with SOP and runbook development and maintenance, incident, problem, and capacity management, business continuity and disaster recovery planning, and proactive risk mitigation • Nice to have: Kubernetes infrastructure, KVM/VMware/OpenShift virtualization, Ansible, NVIDIA Base Command Manager, Slurm or HPC schedulers, Prometheus/Grafana/OpenTelemetry, DCIM, IPAM, and AWS/Azure/hybrid cloud exposure • Not seeking candidates primarily focused on CI/CD, Terraform, GitOps, application delivery pipelines, cloud-only administration, or software development • Deep Linux, infrastructure, storage, BMaaS, and AI Factory expertise is the primary requirement

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