Staff Software Engineer (Infrastructure Storage)

Lambda; United States; Hybrid; USD 180,000 - 240,000; Full time

Job summary

Lambda, The Superintelligence Cloud, is building the world’s leading AI cloud infrastructure with a focus on high-performance storage, networking, and compute to enable large-scale AI research. We are seeking a seasoned Staff Storage Software Engineer to design and deploy storage protocol solutions across object, block, and file paradigms, powering petabyte-scale deployments.

Join a team that steers architecture across storage, networking, compute, and control plane, shaping the future of AI

Qualifications

• Seasoned professional with deep experience in designing and deploying storage protocol solutions at scale across object, block, and file paradigms.
• Proven ability to lead architecture discussions and mentor engineers.
• Strong understanding of distributed storage systems and performance tuning.

Responsibilities

• Provide technical leadership for storage software architecture across petabyte-scale deployments.
• Design and maintain high-performance storage systems across file, block, and object protocols; integrate with NVMe/GPU-direct/DPU-accelerated hardware.

Skills

Technical leadership

Distributed storage

Storage protocols

Cross-functional collaboration

Design docs

Job description

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.

If you'd like to build the world's best AI cloud, join us.*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.

In the world of distributed AI, raw GPU and CPU horsepower is just a part of the story. High-performance networking and storage are the critical components that enable and unite these systems, making groundbreaking AI training and inference possible.

The Lambda Infrastructure Engineering organization forges the foundation of high-performance AI clusters by welding together the latest in AI storage, networking, GPU and CPU hardware.

Our expertise lies at the intersection of:

High-Performance Distributed Storage Solutions and Protocols:

We engineer the protocols and systems that serve massive datasets at the speeds demanded by modern clustered GPUs.

Dynamic Networking:

We design advanced networks that provide multi-tenant security and intelligent routing without compromising performance, using the latest in AI networking hardware.

Compute Virtualization:

We enable cutting-edge virtualization and clustering that allows AI researchers and engineers to focus on AI workloads, not AI infrastructure, unleashing the full compute bandwidth of clustered GPUs.

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 is a unique opportunity to work at the intersection of large-scale distributed systems and the rapidly evolving field of artificial intelligence infrastructure. This is an opportunity to have a significant impact on the future of AI. You will be building the foundational infrastructure that powers some of the most advanced AI research and products in the world.

What You'll Do:

• 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 domai