Senior / Staff NFS Engineer

DDN
Santa Clara Colocation, US
Hybrid

Who this role is best for

Geared toward systems engineers with deep NFS and distributed storage expertise comfortable with low-level I/O optimization and high-speed networking.

Best fit for

  • Candidates with deep systems-level NFS and distributed storage experience, especially those who have debugged I/O stacks in production environments.
    — “Strong hands-on experience with Network File Systems (NFS)”
  • Individuals who have built and debugged storage systems at a kernel and user-space level, with a focus on performance and reliability.
    — “Experience working on kernel-level and/or user-space I/O stacks”
  • Engineers who have integrated storage platforms into Kubernetes environments and developed Python-based tooling for observability and testing.
    — “Develop tooling and automation in Python to improve observability, testing, and operations”

Things to consider

  • The position demands a strong systems mindset, with a focus on performance under real-world load rather than theoretical scenarios.
    — “Your work will directly influence how high-performance data platforms behave under real-world load, not just in theory.”

How to stand out

  • Highlight specific projects where you optimized NFS performance or debugged distributed storage systems.
    — “Design, build, and optimize features across DDN’s NFS and storage stack”
  • Demonstrate experience with low-level I/O stack tuning, particularly in kernel and user-space components.
    — “Work across kernel-space and user-space components to solve hard systems problems”
  • Emphasize your ability to shape infrastructure for AI and data-intensive workloads, not just maintain it.
    — “Help shape the next generation of infrastructure for AI and data-intensive workloads”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • designing and optimizing features
  • diagnosing bottlenecks
  • improving performance and scalability
Typical background
computer sciencesoftware engineering

Skills & requirements

Required

Network File SystemsDistributed File SystemsObject StorageKubernetesPython

Preferred

NvmeSsdsRDMAHigh-speed Networking

Stack & domain

Network File Systems (nfs)Distributed File SystemsObject StorageKubernetesPythonKernel-level I/O StacksUser-space I/O StacksNvmeSsdsRDMAHigh-speed NetworkingStorage PlatformsKubernetes-native EnvironmentsPerformance TuningScalabilityResiliencyDistributed Storage EnvironmentsObservabilityTestingOperationsProblem-solvingCollaborationDebuggingPerformance OptimizationReliabilitySystems ThinkingLow-level Systems WorkDeep Storage/filesystem OwnershipInfrastructure InternalsEngineering DepthStorageNetworkingAIData-intensive WorkloadsInfrastructure

About the role

Original posting from DDN via Ashby

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

Source: DDN careers (Ashby)

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