Senior Software Engineer - Infrastructure Storage

Stack

Responsibilities

• ▹Design, develop and maintain storage system software focusing on performance, scalability and reliability
• ▹Implement and optimize storage protocol APIs for file (NFS, SMB), block (iSCSI, Fibre Channel) and object (S3) access
• ▹Develop distributed systems to manage and orchestrate storage resources across solutions and redundant arrays
• ▹Collaborate with hardware and system architects to integrate software with storage solutions (NVMe, GPU-direct storage)
• ▹Troubleshoot and debug complex issues in a production data center environment
• ▹Contribute to the full software development lifecycle, from requirements to deployment and maintenance

Requirements

• ▹Bachelor's or Master's degree in Computer Science or related field
• ▹5+ years of software development experience in storage systems
• ▹Proven experience with distributed systems programming (load balancers, data durability, consensus algorithms, fault tolerance, data consistency)
• ▹Strong programming skills in C, C++, Go or Python
• ▹Deep understanding of storage protocols: File (NFS, SMB, Lustre), Block (iSCSI, Fibre Channel), Object (S3, Swift)
• ▹Experience with Linux kernel internals and system-level programming
• ▹Familiarity with containerization (Docker, Kubernetes) and running production workloads
• ▹Familiarity with CI/CD and QA practices for distributed systems

Nice to have

• ▹Experience with AI/ML workloads and their storage challenges
• ▹Knowledge of data center networking and high-speed interconnects (InfiniBand, RoCE)
• ▹Experience with storage performance tuning and optimization
• ▹Familiarity with hardware acceleration (GPUs, DPUs)

Soft skills

What we offer

• ▹Generous cash and equity compensation
• ▹Health, dental and vision coverage
• ▹Wellness and commuter stipends
• ▹401k plan with 2% company match
• ▹Flexible paid time off

About the company

Lambda's Infrastructure Engineering organization forges the foundation of high-performance AI clusters, welding together the latest AI storage, networking, GPU and CPU hardware; the Storage team ensures data powering AI is fast, performant and available.