Senior / Staff NFS Engineer

DDN; Sacramento (CA); On-site; USD 180,000 - 230,000; Full time

Job summary

DDN is seeking a senior storage systems engineer in California to design, implement, and optimize high-performance NFS and storage features. You will diagnose complex bottlenecks across kernel-space and user-space I/O paths, and collaborate with teams across storage, systems, and platform layers.

The role emphasizes hands-on development and observable improvements under real workloads. You will leverage Python to automate testing, debugging, and operations, shaping infrastructure for AI and

Qualifications

• Experience operating NFS in production environments.
• Proven experience with distributed file systems and object storage.
• Strong understanding of performance debugging across storage, network, and I/O paths.

Responsibilities

• Design, build, and optimize features across DDN’s NFS and storage stack.
• Diagnose bottlenecks across file systems, storage media, networking, and I/O paths.
• Improve performance, scalability, and resiliency in distributed storage environments.
• Work across kernel-space and user-space components to solve hard systems problems.
• Collaborate with engineers across storage, systems, and platform layers.
• Develop tooling and automation in Python to improve observability, testing, and operations.
• Help shape the next generation of infrastructure for AI and data-intensive workloads.

Skills

NFS expertise

Distributed file systems

Object storage

Python scripting

Kernel-space I/O stacks

User-space I/O stacks

NVMe/SSD

RDMA

Performance debugging

Tools

Kubernetes

Job description

Why this role is compelling

At DDN, you will work on problems that sit at the heart of modern infrastructure:

• Scaling and optimizing Network File Systems
• Building and improving distributed file systems and object storage
• Tuning performance across kernel-level and user-space I/O stacks
• Working with NVMe, SSDs, RDMA, and high-speed networking
• Integrating storage platforms into Kubernetes-native environments
• Using Python to automate, debug, test, and improve complex systems

Your work will directly influence how high-performance data platforms behave under real-world load, not just in theory.

What you’ll do

• Design, build, and optimize features across DDN’s NFS and storage stack
• Diagnose bottlenecks across file systems, storage media, networking, and I/O paths
• Improve performance, scalability, and resiliency in distributed storage environments
• Work across kernel-space and user-space components to solve hard systems problems
• Collaborate with engineers across storage, systems, and platform layers
• Develop tooling and automation in Python to improve observability, testing, and operations
• Help shape the next generation of infrastructure for AI and data-intensive workloads

What we’re looking for

• Strong hands-on experience with Network File Systems (NFS)
• Deep understanding of distributed file systems
• Experience with object storage
• Production experience with Kubernetes
• Strong Python skills
• Experience working on kernel-level and/or user-space I/O stacks
• Familiarity with NVMe, SSDs, RDMA, and high-speed networking
• A systems mindset: you know how to debug complex performance and reliability issues across layers

You’ll thrive here if

• You are energized by low-level systems work
• You like solving problems most engineers avoid because they are too deep, too subtle, or too performance-sensitive
• You care about the details of how storage and networking behave under pressure
• You want your work to matter in environments where performance is mission-critical

This role is probably not for you if

• Your background is primarily general backend, SRE, or platform engineering without deep storage/filesystem ownership
• You’ve used storage systems, but haven’t built or debugged them at a systems level
• You prefer abstraction layers over getting hands‑on with performance, I/O paths, and infrastructure internals
• You want a role focused on coordination more than engineering depth