Staff Engineer, Lustre

About the Position

Staff Engineer, Lustre

We are seeking a Staff Engineer with 10+ years of experience in distributed storage and Linux-based systems engineering. This is a hands-on senior technical role focused on design, debugging, performance, and operational excellence across LustreFS and adjacent stack components. The ideal candidate brings strong expertise in one or more Lustre subsystems, can independently drive complex investigations, and collaborates effectively across engineering, QE, support, and release teams. Engineers who are comfortable using AI to accelerate triage, debugging, code comprehension, and new feature design will be especially valuable.

Location

Santa Clara Office

Employment Type

Full time

Location Type

Hybrid

Department

Department: Engineering, ExaScaler Engineering

Compensation

• $200K – $250K

Key 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.
• Help document subsystem behavior, debugging approaches, known failure patterns, and operational best practices.
• Use AI-assisted tools where appropriate to speed up issue triage, summarize logs, improve code understanding, and capture reusable lessons learned.

Required Qualifications

• 10+ years of experience in systems software, distributed systems, storage, Linux kernel, or filesystem engineering.
• Strong experience in LustreFS development, support, or performance engineering with depth in at least one major subsystem.
• Strong C programming and Linux systems debugging skills.
• Working knowledge of Linux kernel internals, filesystem semantics, networking, and performance analysis.
• Experience with LNet and/or high-performance transports such as RDMA, InfiniBand, RoCE, or TCP-based storage networking.
• Ability to debug and resolve issues spanning multiple layers including client, server, network, and backend storage.
• Strong collaboration skills and the ability to work across functions in a fast-moving engineering environment.

Preferred Skills

• Experience in HPC, AI infrastructure, or large-scale parallel storage environments.
• Exposure to metadata-heavy and throughput-heavy workload characterization and tuning.
• Familiarity with ZFS, ldiskfs, NVMe-backed storage, and related observability/performance tooling.
• Experience creating test plans, reproducer frameworks, runbooks, or diagnostic automation.
• Comfort using AI tools to accelerate debugging, code reviews, triage, documentation, and early-stage design ideation.
• Experience mentoring junior engineers or leading focused technical efforts within a subsystem.

What You Will Work On

• Hands-on development and debugging of LustreFS defects, performance issues, and subsystem enhancements.
• Customer-facing and scale-related issue investigation across llite, metadata, object storage, LNet, and transport layers.
• Collaborative design and implementation of reliability, observability, and serviceability improvements.
• Reviewing and validating fixes through targeted tests, failure injection, log analysis, and performance characterization.
• Using AI-assisted workflows to accelerate triage, debug loops, code understanding, and documentation quality.
• Contributing to team redundancy by strengthening documentation, code review quality, and subsystem knowledge sharing.

Why This Role Matters

This role is central to building durable engineering redundancy in LustreFS: expanding deep subsystem ownership, reducing concentration risk, and accelerating next-generation delivery through strong engineering fundamentals and AI-enabled execution.

Compensation Range: $200K - $250K