Storage Engineer

TensorWave•Las Vegas, NV

About The Position

We are looking for a Storage Engineer with deep expertise in NFS-based storage and modern high-performance file systems, specifically VAST Data and WEKA. This role exists to ensure our shared storage platforms are fast, reliable, scalable, and boring — even under extreme load. You will own the design, operation, and performance of our file storage layer, supporting workloads that depend on low latency, high throughput, and predictable behavior. This is a hands-on role for someone who understands storage at the protocol and system level, not just from a dashboard. If you think in terms of NFS semantics, metadata performance, failure domains, and throughput per node, this role is for you.

Requirements

Strong hands-on experience with NFS in production environments
Direct experience operating VAST Data and/or WEKA systems
Deep understanding of distributed file systems and shared storage architectures
Strong knowledge of storage performance fundamentals (latency, throughput, metadata operations)
Experience troubleshooting complex storage and networking interactions
Solid Linux systems knowledge, especially around filesystem and I/O behavior
Ability to reason about failure domains, recovery paths, and data integrity

Nice To Haves

Experience supporting AI/ML, HPC, or data-intensive workloads
Familiarity with RDMA, high-speed networking, or NVMe-based storage
Kubernetes workloads backed by shared file system
Experience with multi-rack or multi-site storage deployments
Infrastructure-as-Code experience or automation experience

Responsibilities

Design, deploy, and operate NFS-based storage systems for production workloads
Own and operate VAST Data and WEKA clusters in production environments
Architect storage for high-throughput, low-latency shared file access
Tune and optimize NFS performance (mount options, client behavior, server-side tuning)
Manage capacity planning, scaling, and rebalancing for VAST and WEKA systems
Diagnose and resolve storage performance issues (latency spikes, metadata bottlenecks, throughput drops)
Design and test failure and recovery scenarios (node failures, network issues, disk loss)
Lead upgrades, expansions, and maintenance with minimal or zero downtime
Partner with infrastructure and application teams to ensure workloads are well-matched to storage behavior
Document operational runbooks and establish best practices for shared file storage