Staff Storage Engineer

Mural Group; San Francisco (CA); On-site; USD 220,000 - 400,000; Full time

Job summary

Mural Group seeks a storage engineer to shape the data layer for its AI inference platform. You will design distributed storage solutions, deploy high-performance file systems, and optimize capacity for demanding AI workloads across multiple onsite locations (Dallas, SF, or New York).

Ideal candidates bring 8+ years in large-scale storage, hands-on WEKA/VAST in AI/HPC, strong NVMe expertise, and Python automation skills. This role offers a competitive salary with bonus and equity, onsite only.

Qualifications

• 8+ years designing large-scale distributed storage systems.
• Hands-on WEKA and/or VAST in AI or HPC environments.
• Experience with NVMe and NVMe-oF.
• Expertise in storage performance tuning and Linux storage internals.
• Automation of tasks with Python, CI/CD tooling.

Responsibilities

• Design distributed file, object and block storage for AI workloads.
• Deploy and run high-performance parallel file systems.
• Analyze I/O patterns and plan capacity.
• Define durability, erasure coding, backup and DR.
• Benchmark, test failure modes and automate with Python and CI/CD.

Skills

Storage design

Distributed systems

Capacity planning

Benchmarking

CI/CD automation

Tools

WEKA

VAST

NVMe

NVMe-oF

Python

Linux storage internals

Storage performance tuning

GPUDirect Storage

RDMA/RoCEv2

Job description

Location: Dallas, TX; San Francisco, CA; or New York, NY (onsite)

Pay: $220,000–$400,000 + bonus + equity

A high-growth AI infrastructure company needs a storage engineer to shape the data layer for its inference platform.

What you\'ll do

• Design distributed file, object and block storage for AI workloads


• Deploy and run high-performance parallel file systems


• Analyze I/O patterns and plan capacity


• Define durability, erasure coding, backup and DR


• Benchmark, test failure modes and automate with Python and CI/CD

What you bring

• 8+ years designing large-scale distributed storage


• Hands-on WEKA and/or VAST in AI or HPC environments


• NVMe and NVMe-oF


• Storage performance tuning and Linux storage internals


• Python automation

Nice to have: GPUDirect Storage; RDMA/RoCEv2