About the job
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. We are seeking a seasoned Staff Storage Software Engineer with deep experience designing and deploying storage protocol solutions at scale across object, block, and file paradigms. This is a unique opportunity to work at the intersection of large-scale distributed systems and the rapidly evolving field of artificial intelligence infrastructure.
Responsibilities
Set technical direction for storage software architecture across the Infrastructure Engineering organization, influencing decisions that span petabyte-scale deployments.
Design, develop, and maintain high-performance storage systems software with a focus on performance, scalability, reliability, and operational simplicity.
Implement and optimize storage protocol APIs across file, block, and object access patterns.
Collaborate with hardware and system architects to integrate software with storage solutions including NVMe, GPU-direct storage, and DPU-accelerated data paths.
Optimize storage protocol solutions for AI workloads, including checkpoint I/O for training, high-throughput dataset serving, and latency-sensitive inference pipelines.
Qualifications
Minimum
10+ years of experience in storage systems engineering, with at least 5 years in a technical lead or Staff+ IC role.
Proven track record designing and operating storage infrastructure at scale in production data center or cloud settings.
Strong proficiency in one or more low-level systems programming languages: C, C++, Rust, or Go.
Deep hands-on experience with two or more storage protocols: object, block, or file.
Experience profiling and tuning storage systems for throughput, latency, and IOPS under real production workloads.
Comfort working in a physical data center environment and experience building and operating storage systems with strong reliability expectations.
Preferred
Experience with NVIDIA BlueField DPUs or SuperNICs for accelerated storage data paths, including GPUDirect Storage implementation.
Deep production experience with enterprise or HPC storage platforms: Vast Data, Weka, NetApp, or IBM Spectrum Scale.
Experience deploying and operating Ceph at scale (100PB+) in an HPC or AI infrastructure environment.
Familiarity with emerging storage technologies such as CXL memory pooling, computational storage, or ZNS (Zoned Namespace) SSDs.
Experience contributing to or maintaining open-source storage projects (e.g., Ceph, DAOS, Lustre, MinIO).