[Hiring] Software Engineering Lead @Data Direct Networks

Role Description

We are seeking a Software Engineering Lead – NFS with deep expertise in data path and I/O performance for large-scale distributed file systems. This role is for a senior technical leader who drives NFS architecture across the storage stack, from low-level code paths to system-wide behavior at massive scale.

You will define strategy, guide architectural decisions, and lead complex NFS implementation for high-throughput, low-latency distributed systems. This role combines hands-on technical depth with broad architectural influence.

Key Responsibilities

• Define and own architecture for NFS across distributed file systems
• Drive performance analysis and optimization of large-scale, high-performance, scale-out file systems
• Architect performance-aware NFS design and architecture
• Drive optimization of performance-critical distributed file system code, primarily in C++
• Help drive best practices for performance measurement, profiling, benchmarking, and regression detection
• Lead deep-dive investigations into complex, system-wide issues
• Influence system architecture with a performance-first mindset around NFS and accompanying tradeoffs against other protocols
• Mentor senior and staff engineers on engineering techniques and methodologies
• Collaborate with cross-functional teams to ensure goals are met across the stack
• Represent NFS considerations in design reviews and long-term roadmap planning

Qualifications

• 15+ years of experience in NFS engineering, systems engineering, or distributed systems
• Deep understanding of distributed file systems and scale-out storage architectures
• Expert-level knowledge of NFS and distributed file systems
• Strong proficiency in C++ with extensive experience in performance-critical code
• Proven expertise in performance measurement techniques, including profiling, tracing, benchmarking, and custom tooling
• Strong foundation in distributed systems principles, including scalability, concurrency, and fault tolerance
• Demonstrated experience optimizing file system or storage system code for performance at scale
• Experience with high-performance, high-scale-out file systems in production environments

Preferred Qualifications

• Experience with kernel-level and user-space I/O stacks
• Deep understanding of modern storage hardware (NVMe, SSDs, RDMA, high-speed networking)
• Experience building or evolving performance frameworks and benchmarking infrastructure
• Background in parallel programming, lock-free or low-contention designs
• Experience influencing architecture across multiple teams or large codebases

What Success Looks Like

• Clear performance architecture guiding system design and implementation
• Significant, measurable improvements in throughput, latency, and scalability
• Early identification and prevention of performance regressions
• Performance expertise that elevates engineering quality across the organization

Interview Process

After submitting your application, one of our recruiters will review your resume. If your application passes this stage, you will be invited to a 30-minute interview during which a member of our team will ask some basic questions. If you clear the interview, you will enter the main process, which can consist of up to four interviews in total:

• Coding assessment: Often in a language of your choice.
• Systems design: Translate high-level requirements into a scalable, fault-tolerant service (depending on role).
• Real-time problem-solving: Demonstrate practical skills in a live problem-solving session.
• Meet and greet with the wider team.

Our goal is to finish the main process in 2-3 weeks at most.

Company Description

DataDirect Networks (DDN) is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, transgender, sex stereotyping, sexual orientation, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.