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 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.

Responsibilities

• Technical Leadership:
• Set technical direction for storage software architecture across the Infrastructure Engineering organization, influencing decisions that span petabyte-scale deployments.
• Author and review design documents for new storage systems, protocols, and integrations; raise the technical bar across the team.
• Mentor and develop senior engineers, providing guidance on systems design, debugging complex distributed systems issues, and navigating technical tradeoffs.
• Serve as a technical anchor for cross-functional initiatives involving storage, networking, compute, and control plane teams.
• Represent the storage software team in architectural reviews, roadmap planning, and customer-facing technical discussions where needed.
• Execution:
• 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 (NFS, SMB, Lustre), block (NVMe-oF, iSCSI, Fibre Channel), and object (S3) access patterns.
• Develop distributed systems for managing and orchestrating storage resources across multiple solutions and redundant arrays.
• Collaborate with hardware and system architects to integrate software with storage solutions including NVMe, GPU-direct storage, and DPU-accelerated data paths.
• Troubleshoot and resolve complex issues in production data center environments, including performance regressions, protocol mismatches, and hardware failures.
• Contribute across the full software development lifecycle - from requirements gathering and system design through deployment, monitoring, and long-term maintenance.
• Build and maintain tooling for storage benchmarking, performance profiling, and capacity planning.
• Collaboration
• Work closely with storage software and networking teams to execute cross-functional infrastructure initiatives and new data center deployments, including integration of storage protocols across a variety of on-prem solutions.
• Partner with the control plane and Kubernetes teams to meet customer and product requirements for usability, reliability, and telemetry.
• Work with the observability team to define, build, and track SLOs/SLIs for storage systems.
• Coordinate with Networking, Compute, and Storage Engineering teams to deploy high-performance distributed storage solutions that serve AI/ML workloads.
• Partner with the Fleet Engineering team to ensure seamless deployment, monitoring, and ongoing maintenance of distributed storage infrastructure.
• Innovate:
• Stay current with the latest research and developments in AI and HPC storage technologies, and bring relevant advances into Lambda's infrastructure.
• Work with the Lambda product team to identify emerging trends in AI inference and t

Additional Information

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/San Jose/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.

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