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# Senior 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, Cluster Analysis, Computer Programming, Continuous Integration, Data Files, Software Debugging, Distributed Data Store, Distributed Systems, Fault Tolerance, InfiniBand, Networking Hardware, Internet Small Computer System Interface (ISCSI), Python (Programming Language), Linux Kernel, Operational Databases, Performance Tuning, Software Engineering, Virtualization Technology, AI Infrastructure, Graphics Processing Unit (GPU), Load Balancing, AWS Lambda, Fibre Channel, Data Center Networking, Containerization, Storage Technologies, Information Technology, Hardware Acceleration, Machine Learning Operations, Docker, Nvme
- **Published:** November 2, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-infrastructure-storage-san-francisco-ca--6017ed79-f325-418e-8ab3-40f907c849fa

## About the Role

Software Engineering, Cloud Computing, Artificial Intelligence (AI), Electricity, AWS Lambda, Work From Home, GPU (Graphics Processing Unit), CPU (Central Processing Unit), Welding, Data Sets, * Bachelor's or Master's degree in Computer Science or a related field.

 * 5+ years of experience in software development for storage systems.
 * Proven experience with distributed systems programming and concepts such as load balancers, data-durability, consensus algorithms, fault tolerance, and data consistency.
 * Strong programming skills in languages such as C, C++, Go, or Python.
 * Deep understanding of storage protocols, including:
 + File: NFS, SMB, Lustre
 + Block: iSCSI, Fibre Channel
 + Object: S3, Swift
 * Experience with Linux kernel internals and system-level programming.
 * Familiarity with containerization technologies like Docker and Kubernetes and running production workloads in these environments.
 * Familiarity with CI/CD and QA practices for distributed systems development environments.

Nice to Have

 * Experience with AI/ML workloads and the unique storage challenges they present.
 * Knowledge of data center networking and high-speed interconnects (e.g., InfiniBand, RoCE).
 * Experience with performance tuning and optimization of storage systems.
 * Familiarity with hardware acceleration technologies, specifically GPUs and DPUs.

## Description

* 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 Clustering and 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.

AI training and inference relies on petabytes of data hosted on large, high-performance storage arrays. At Lambda, the Infrastructure Storage Team's job is to ensure that the data powering AI is fast, performant, and available across a variety of access protocols (fit for purpose).

We're looking for an experienced Senior Software Engineer to join our storage team. You'll join a team responsible for developing and implementing storage software for our next-generation on-premise storage solutions. This role requires expertise in distributed systems, and an in-depth understanding of file, block, and object storage protocols. You'll work on building scalable and resilient storage services that power our AI and machine learning infrastructure.

What You'll Do:

 * Design, develop, and maintain software for storage systems, focusing on performance, scalability, and reliability.
 * Implement and optimize storage protocol APIs for file (e.g., NFS, SMB), block (e.g., iSCSI, Fibre Channel), and object (e.g., S3) access.
 * Develop distributed systems for managing and orchestrating storage resources across multiple storage solutions and redundant arrays.
 * Collaborate with hardware and system architects to integrate software with various storage solutions, including NVMe and GPU-direct storage.
 * Troubleshoot and debug complex issues in a production data center environment.
 * Contribute to the full software development lifecycle, from requirements gathering and design to deployment and maintenance.