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.
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.
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.
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.
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.
Skills Required
- 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 or high-performance transports such as RDMA, InfiniBand, RoCE, or TCP-based storage networking
- Ability to debug and resolve issues spanning client, server, network, and backend storage layers
- Strong collaboration skills and ability to work across functions in a fast-moving engineering environment
- Experience in HPC, AI infrastructure, or large-scale parallel storage environments
- Experience with metadata-heavy and throughput-heavy workload characterization and tuning
- Familiarity with ZFS, ldiskfs, NVMe-backed storage, and observability or performance tooling
- Experience creating test plans, reproducer frameworks, runbooks, or diagnostic automation
- Comfort using AI tools for debugging, code reviews, triage, documentation, and design ideation
- Experience mentoring junior engineers or leading focused technical efforts within a subsystem
What We Do
DDN is the world’s largest private data storage company and the leading provider of intelligent technology and infrastructure solutions for Enterprise At Scale, AI and analytics, HPC, government and academia customers. Through its DDN and Tintri divisions, the company delivers AI, Data Management software and hardware solutions, and unified analytics frameworks to solve complex business challenges for data-intensive, global organizations. DDN provides its enterprise customers with the most flexible, efficient and reliable data storage solutions for on-premises and multi-cloud environments at any scale. Over the last two decades, DDN has established itself as the data management provider of choice for over 11,000 enterprises, government, and public-sector customers, including many of the world’s leading financial services firms, life science organizations, manufacturing and energy companies, research facilities, and web and cloud service providers.
