AI summary
This role involves deploying, integrating, and maintaining high-performance storage systems for GPU-accelerated environments, primarily utilizing Kubernetes, Linux, and NFS technologies. The engineer will automate storage operations and optimize performance to support demanding workloads.
Job Description
Overview
The role is to deploy, integrate, and operate high-performance storage for GPU-accelerated compute and AI platforms. You will own the storage layer where Kubernetes meets bare metal — standing up NFS-based high-performance storage, wiring it into clusters via CSI, and tuning it to keep data flowing to GPU workloads at scale. Work spans hybrid, edge, and air-gapped deployments built on the Mirantis K0rdent stack.
About the Role
We are looking for a senior systems engineer who treats storage as infrastructure to be automated, observed, and tuned — not hand-managed. The right candidate is fluent in Kubernetes storage, deeply versed in Linux storage and networking fundamentals down to the kernel and NFS-client layer, and knows how to make high-performance NAS actually perform under demanding workloads. You should reach for infrastructure-as-code and GitOps by default, be self-directed in diagnosing performance and reliability issues end to end, set operational standards for others to follow, and communicate clearly across teams. Bare-metal hardware experience is a strong plus, but deep Linux storage knowledge is essential.
Responsibilities
1. Storage Integration & Operation
- Integrate NFS-based high-performance storage (e.g., VAST, Dell PowerScale) into Kubernetes clusters via CSI, storage classes, and persistent volumes.
- Tune the NFS data path — mount options, nconnect/RDMA, Linux client, and network settings — for high-throughput, low-latency GPU/AI workloads.
- Deploy and operate storage services and operators; manage capacity, quotas, snapshots, and lifecycle.
2. Linux Platform & System Integration
- Configure and optimize Linux systems for storage workloads, including driver setup, file system layout, network tuning, and kernel parameter optimization.
- Deliver storage integration for k0s-based Kubernetes via Cluster API (CAPI) and K0rdent management/child cluster topologies.
- Operate storage in fully disconnected (air-gapped) environments, including local artifact/mirror connectivity (Harbor) and PKI/TLS considerations.
3. Automation & Observability
- Automate storage provisioning and configuration with infrastructure-as-code (Terraform/OpenTofu) and GitOps pipelines (ArgoCD or Flux).
- Build monitoring, alerting, and observability for storage performance, capacity, and health.
- Diagnose and resolve performance, reliability, and scaling issues across the storage stack.
Requirements
Required qualifications:
- 7+ years of experience in SRE or hardware/storage infrastructure operations
- 5+ years of building/operating distributed production Storage systems at scale
- 7+ years of experience in Linux and K8s storage fundamentals (NFS, CSI)
- 1+ years of experience integrating with or building High Performance Storage solutions (VAST, Weka, DDN, PowerScale)
About the job
- Posted on
- Sep 4, 2026
- Job type
- Full-time
- Location
- Remote, USA, usRemote
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