Infrastructure Engineer – Storage Platform

TensorWave•Las Vegas, NV

About The Position

TensorWave is building and operating large-scale infrastructure platforms to support high-performance AI and machine learning workloads across multiple data centers. Their environment includes GPU-intensive systems, high-throughput networking, and distributed storage platforms designed for performance, scale, and resilience. They are looking for a Storage Operations Engineer to own the day-to-day operation, performance, and reliability of their storage platforms. This role is responsible for ensuring that storage systems remain stable, performant, and aligned with the demands of Kubernetes, AI/ML, and high-performance compute workloads. This is not a traditional SAN/NAS administration role. The engineer will work with modern distributed storage systems and be expected to troubleshoot, optimize, and scale them in production environments.

Requirements

4–7+ years of experience in infrastructure, systems, or storage operations
Strong hands-on experience operating distributed storage systems in production
Experience with Ceph (RBD, CephFS, or RGW)
Experience with modern storage platforms such as: Weka, VAST Data, or similar high-performance systems
Strong Linux systems knowledge
Solid understanding of storage performance characteristics (IOPS, throughput, latency)
Solid understanding of data replication and failure domains
Ability to troubleshoot across storage systems
Ability to troubleshoot across network paths
Ability to troubleshoot across compute clients

Nice To Haves

Experience supporting AI/ML or HPC workloads
Familiarity with NVMe-based storage architectures
Familiarity with RDMA or high-throughput Ethernet environments
Experience integrating storage with Kubernetes
Experience operating storage across multiple data centers
Exposure to object storage and S3-compatible APIs

Responsibilities

Operate and maintain distributed storage platforms, including Ceph (RBD, CephFS, RGW), High-performance NAS platforms (e.g., Weka, VAST Data)
Manage storage lifecycle operations - cluster expansion, upgrades and migrations
Monitor and maintain storage health, including capacity utilization, data distribution and balance, cluster state and recovery operations
Analyze and troubleshoot storage performance across IOPS, throughput, and latency (including tail latency)
Identify and remediate bottlenecks across disk subsystems, network paths (including RDMA where applicable), client access patterns
Support incident response and root cause analysis for storage-related issues
Ensure storage platforms meet performance expectations for GPU and Kubernetes workloads
Operate and support Kubernetes-integrated storage - CSI drivers, StorageClasses, PersistentVolumes / PersistentVolumeClaims
Troubleshoot storage-related issues in Kubernetes environments, including stateful workloads, performance inconsistencies, scheduling and provisioning failures
Execute and improve automation for storage deployment and operations using Ansible, Terraform, Kubernetes manifests / Helm
Contribute to improving monitoring and alerting, operational workflows, runbooks and documentation
Partner with DevOps and Platform Engineering (automation and orchestration), Network Engineering (high-throughput and RDMA networking), Compute / Virtualization teams
Help ensure end-to-end performance across compute, network, and storage layers

Benefits

Stock Options
100% paid Medical, Dental, and Vision insurance for Employees
Company Health Savings Account Contributions
100% paid Short Term and Long Term Disability Insurance for Employees
Life and Voluntary Supplemental Insurance Options
Other Insurance Options, such as Pet & Legal Insurance
Various Supplementary Health Benefits, such as discounted Virtual Healthcare Appointments and Serious Illness Support
Flexible Spending Account
401(k)
Employee Assistance Program
Flexible PTO
Paid Holidays
Parental Leave
Other In-Office Perks