Senior Storage Systems Engineer - remote in the US

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 company 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.

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)

What does the company 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.

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We are a  Leader for Container Management  in G2 (#2 after AWS)!

About the company

The company 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, the company 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, the company 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, the company ensures that customers retain full control of their infrastructure strategy.