Software Engineer - Infrastructure Storage

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.

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.

• 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 training that will shape next‑generation storage requirements.
  • Evaluate and prototype new storage solutions, protocols, and hardware integrations - from open‑source distributed file systems to vendor‑specific accelerated storage products.
  • Optimize storage protocol solutions for AI workloads, including checkpoint I/O for training, high‑throughput dataset serving, and latency‑sensitive inference pipelines.

• Experience

  • 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 (multi‑petabyte environments preferred) in production data…