Senior Staff Engineer, LustreFS — Hybrid & AI-Driven Debug

DataDirect Networks; Santa Clara (CA); Hybrid; USD 200,000 - 250,000; Full time

Benefits offered by this job

Highly Competitive Vacation Plans

Paid Holidays

Bonus Programs

Tuition Reimbursement

Employee Referral Program

Excellent Medical, Dental and Vision  

Paid Leave Programs

Anniversary and Recognition Awards

Job summary

DataDirect Networks is seeking a Staff Engineer with 10+ years of experience in distributed storage and Linux-based systems engineering to design, debug and optimize LustreFS. You will own complex investigations, work across LLite, MDS/MDT, and transport layers, and drive reliability at scale.

The role emphasizes hands-on development, collaboration with QE and support, and the use of AI-assisted tooling to accelerate triage and design improvements.

Qualifications

• 10+ years of experience in systems software, distributed systems, storage, Linux kernel or filesystem engineering.

Responsibilities

• Design, develop and debug LustreFS features, fixes and enhancements across relevant subsystems such as llite, MDS/MDT, OSS/OST, LDLM and LNet.
• Investigate customer and scale-related defects, drive root-cause analysis and implement high-quality fixes with strong attention to correctness and maintainability.
• Contribute to performance tuning, failure analysis and reliability improvements for large-scale Lustre deployments.
• Participate actively in code reviews, design reviews and subsystem discussions, bringing rigor to testing and operational readiness.
• Work closely with QE and support to reproduce issues, improve diagnostic data quality and increase coverage for high-risk failure scenarios.

Job description

DataDirect Networks is seeking a Staff Engineer with 10+ years of experience in distributed storage and Linux-based systems engineering to design, debug and optimize LustreFS. You will own complex investigations, work across LLite, MDS/MDT, and transport layers, and drive reliability at scale.

The role emphasizes hands-on development, collaboration with QE and support, and the use of AI-assisted tooling to accelerate triage and design improvements.