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# Staff Software Engineer - Infrastructure Storage

- **Company:** Lambda Inc.
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon S3, C++ (Programming Language), Cloud Computing, Cloud Storage, Profiling, Computer Programming, Data Centers, Data Files, Distributed Data Store, Distributed Systems, InfiniBand, Internet Small Computer System Interface (ISCSI), NetApp Applications, Network Control, Open Source Technology, Operational Databases, Remote Direct Memory Access, Prometheus, Runbook, Software Engineering, Weka, AI Infrastructure, Ceph (Software), Datadog, Graphics Processing Unit (GPU), Cloud Platform System, Grafana, AWS Lambda, Kubernetes, Storage Technologies, Low Latency, Machine Learning Operations, Nvme
- **Published:** November 6, 2026
- **Apply:** https://www.careerbuilder.com/job-details/staff-software-engineer-infrastructure-storage-san-francisco-ca--71dee189-5ff2-4004-884a-6bb4625a3df9

## About the Role

Software Engineering, Cloud Computing, Artificial Intelligence (AI), Electricity, AWS Lambda, Work From Home, CPU (Central Processing Unit), GPU (Graphics Processing Unit), Welding, Data Sets, * Experience: 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.

 * Systems-Level Programming: Strong proficiency in C, C++, Rust, or Go. Ability to write high-performance, concurrent, production-grade systems code. Familiarity with DPDK/SPDK and kernel-bypass data paths is a plus; kernel-level storage driver or storage daemon experience is even better.
 * Storage Protocol & API Expertise: Deep hands-on experience with two or more protocols, object (S3), block (iSCSI, NVMe-oF), or file (NFS, SMB, Lustre, DAOS), including implementing or maintaining protocol servers/clients in production, not just consuming them.
 * Storage Performance Optimization: Experience profiling and tuning for throughput, latency, and IOPS under real workloads using tools like fio, elbencho.
 * Modern Storage Technologies: Working knowledge of NVMe, NVMe-oF, RDMA (RoCE or InfiniBand), and DPUs (e.g., NVIDIA BlueField).
 * Operational Acumen: Comfortable in physical data center environments, rack-scale infrastructure, storage hardware, failure domains. Experience designing for reliability, writing runbooks, and driving incident response. Familiar with storage observability tooling (Prometheus, Grafana, log aggregation, tracing).

Nice to Have

 * 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 service 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).

## Description

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., * Technical Leadership: Set technical direction for storage software architecture across petabyte-scale deployments, authoring and reviewing design docs, mentoring senior engineers, and serving 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 across performance, protocol, and hardware failure domains. Own the full lifecycle from requirements and design through deployment, monitoring, and maintenance, including 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 and maintenance of distributed storage infrastructure.
 * Innovate: Stay current with AI and HPC storage research, evaluate emerging protocols and hardware (from open-source filesystems to vendor-specific accelerated storage), and optimize solutions for AI workloads including checkpoint I/O, high-throughput dataset serving, and latency-sensitive inference pipelines.