Staff Software Engineer - Infrastructure Storage

About the Role

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 role works at the intersection of large-scale distributed systems and artificial intelligence infrastructure, building foundational infrastructure that powers advanced AI research and products.

*Note: This position requires presence in our San Francisco/Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.*

What You’ll Do

• Technical Leadership: Set technical direction for storage software architecture across petabyte-scale deployments, author and review design docs, mentor senior engineers, and serve as the technical anchor for cross-functional initiatives spanning storage, networking, compute, and control plane teams. Represent the storage software team in architectural reviews, roadmap planning, and customer-facing technical discussions.
• Execution: Design, develop, and maintain high-performance storage systems software across file (NFS, SMB, Lustre), block (NVMe-oF, iSCSI), and object (S3) protocols. Build distributed systems for orchestrating storage resources, integrate with NVMe/GPU-direct/DPU-accelerated hardware, and troubleshoot complex production issues. Own the full lifecycle from requirements and design through deployment, monitoring, maintenance, benchmarking, profiling, and capacity planning tooling.
• Collaboration: Partner closely with storage software, networking, control plane, Kubernetes, observability, compute, and fleet engineering teams to deliver cross-functional infrastructure initiatives, define and track storage SLOs/SLIs, and ensure reliable deployment of distributed storage infrastructure.
• Innovate: Stay current with AI and HPC storage research, evaluate emerging protocols and hardware, and optimize solutions for AI workloads including checkpoint I/O, high-throughput dataset serving, and latency-sensitive inference pipelines.

Qualifications

Required

• 10+ years in storage systems engineering, with 5+ years in a technical lead or Staff+ IC role.
• Proven track record designing and operating multi-petabyte storage infrastructure in production data center or cloud environments.
• Background in HPC, AI/ML infrastructure, or large-scale cloud storage.
• Strong proficiency in C, C++, Rust, or Go with the ability to write high-performance, concurrent, production-grade systems code.
• Deep hands-on experience implementing or maintaining protocol servers/clients in production across two or more protocols: object (S3), block (iSCSI, NVMe-oF), or file (NFS, SMB, Lustre, DAOS).
• Experience profiling and tuning storage for throughput, latency, and IOPS under real workloads using tools like `fio` and `elbencho`.
• Working knowledge of NVMe, NVMe-oF, RDMA (RoCE or InfiniBand), and DPUs (e.g., NVIDIA BlueField).
• Experience with physical data center environments, rack-scale infrastructure, storage hardware, failure domains, reliability design, runbooks, and incident response.
• Familiarity with storage observability tooling (Prometheus, Grafana, log aggregation, tracing).

Preferred

• Familiarity with DPDK/SPDK and kernel-bypass data paths; kernel-level storage driver or storage daemon experience.
• 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 Lustre.
• Experience deploying and operating Ceph-like services 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).