AI Storage Infrastructure Engineer - remote in the US

Mirantis; United States; On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Competitive pay

Benefits plan

Professional development

Job summary

Mirantis in California is seeking a senior systems engineer to deploy, integrate, and operate high-performance storage for GPU-accelerated AI workloads. You will own the storage layer where Kubernetes meets bare metal, wiring NFS-based storage into clusters via CSI and tuning for throughput and low latency.

The ideal candidate has deep Linux storage knowledge, hands-on Kubernetes storage experience, and a habit of infrastructure-as-code and GitOps.

Qualifications

• 7+ years of experience in SRE or hardware/storage infrastructure operations.
• 5+ years building/operating distributed production storage systems.
• 7+ years Linux and Kubernetes storage fundamentals (NFS, CSI).
• 1+ years experience with high-performance storage solutions (VAST, Weka, DDN, PowerScale).

Responsibilities

• Storage integration and operation across clusters via CSI and storage classes.
• Tune NFS data path for high-throughput GPU/AI workloads.
• Deploy and operate storage services and manage capacity, quotas, snapshots.
• Configure Linux systems for storage workloads and kernel tuning.
• Deliver storage integration for k0s-based Kubernetes via CAPI and Mirantis K0rdent.
• Operate storage in air-gapped environments with Harbor and PKI/TLS considerations.
• Automate provisioning with Terraform/OpenTofu and GitOps pipelines.

Skills

SRE/Storage Ops

Distributed storage

Linux storage

Kubernetes storage

High performance storage

Tools

VAST

Weka

DDN

PowerScale

Job description

About Mirantis

Mirantis is the Kubernetes-native AI infrastructure company, enabling organizations to build and operate scalable, secure, and sovereign infrastructure for modern AI, machine learning, and data-intensive applications. By combining open source innovation with deep expertise in Kubernetes orchestration, Mirantis empowers platform engineering teams to deliver composable, production-ready developer platforms across any environment—on-premises, in the cloud, at the edge, or in sovereign data centers. As enterprises navigate the growing complexity of AI-driven workloads, Mirantis delivers the automation, GPU orchestration, and policy-driven control needed to manage infrastructure with confidence and agility. Committed to open standards and freedom from lock-in, Mirantis ensures that customers retain full control of their infrastructure strategy.

Job Description

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

• 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.
• 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.
• 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.

Qualifications

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)

Additional Information

What does Mirantis offer you?

• Work with an established Silicon Valley leader in the cloud infrastructure industry
• Work with exceptionally passionate, talented and engaging colleagues, helping Fortune 500 and Global 2000 customers implement next-generation cloud technologies
• Be a part of cutting-edge, open-source innovation
• Thrive in the high-energy environment of a young company where openness, collaboration, risk-taking, and continuous growth are valued
• Professional development and training
• Attend conferences and working groups
• Company outings, happy hours, hackathons, and tech talks
• Receive a competitive compensation package with a strong benefits plan

It is understood that Mirantis, Inc. may use automated decision-making technology (ADMT) for specific employment-related decisions. Opting out of ADMT use is requested for decisions about evaluation and review connected with the specific employment decision for the position applied for. You also have the right to appeal any decisions made by ADMT by sending your request to [e-mail]

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