Overview
If you know where NFS breaks at scale — and you enjoy fixing it deep in the storage stack — this is the kind of role that rarely comes along.
DDN is building infrastructure for some of the world’s most demanding AI, data, and performance-intensive environments. We are looking for a Bay Area–based NFS Engineer who wants to work where distributed systems, file systems, object storage, Kubernetes, and high-speed networking all collide.
This is not a role for someone who has only touched storage from the outside. It is for an engineer who has lived close to the metal, understands how data moves through kernel and user-space I/O paths, and wants to push performance, reliability, and scale in real production systems.
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
Salary Range: $123,000 - $266,100
DDN
Why DDN - DDN is where serious infrastructure engineers go to work on serious data problems. If you want to be part of a team solving challenges at the intersection of storage, distributed systems, and performance engineering — and you want to do it in an environment that values technical depth — we should talk.
Apply if - You’re a Bay Area or RTP based engineer with deep NFS and storage systems expertise, and you want to build technology that operates at the highest levels of scale and performance.
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