High-performance networking and storage are essential for interconnecting these systems and supporting AI training and inference at scale.\n \nLambda's Infrastructure Engineering team integrates advanced storage, networking, and compute hardware to build high-performance clusters.\n \nOur expertise lies at the intersection of:\n\n High-Performance Distributed Storage Solutions: We deploy and maintain the storage systems that provide customer training and inference datasets at the speeds demanded by modern clustered GPUs.\n \n\n Software Defined Networking: We deploy software defined network overlays that provide multi-tenant security and intelligent routing without compromising performance, using the latest in high-performance networking hardware.\n \n\n Compute Virtualization: We enable virtualization that allows AI researchers and engineers to focus on AI workloads, not AI infrastructure.\n \n\n Cluster Integrity: We own the cluster integrity lifecycle: validating deployments, diagnosing performance and health across hardware and fabrics, and providing proactive remediation.\n \n\n \nAbout the Role:\n \nYou will focus on strategy, architecture, and organizational influence\n\n Strategic Selection: Lead the RFP process and drive evidence-based storage solution selection and vendor evaluations.\n \n\n Workload Optimization: Develop an in-depth understanding of AI/ML workload profiles to influence future storage architecture and performance tuning.\n \n\n Operational Strategy: Identify and lead high-impact operational improvements and cross-functional deployment plans.\n \n\n Customer Discovery: Partner with leadership during deal formation to gather technical requirements and inform solution design.\n \n\n Organizational Leadership: Delegate complex engineering tasks and maintain consistent, proactive communication with the engineering leadership team.\n \n\n \nYou Have:\n\n 8+ years of experience designing, building, and operating large-scale multi-petabyte storage production environments\n \n\n A strong understanding of diverse storage solutions and their ecosystems:\n Familiarity with one or more storage solutions of the following vendors: Vast, Weka, DDN, NetApp, PureStorage, Dell, IBM, HPE\n \n\n File, Block, and Object storage types\n \n\n Storage Network Access Protocols such as NFS, SMB, and POSIX-compliant protocols.\n \n\n NVMEoverFabricStorage Transport Protocols: NVME/TCP, NVME/IB, or NVME/RoCE\n \n\n Storage performance via RDMA, GPUDirect Storage, parallel file systems\n \n\n Encryption, storage security, and multi-tenancy strategies\n \n\n Storage data-reduction, compression, and encryption\n \n\n Backup and data protection\n \n\n \n\n 5+ years of experience in Infrastructure as Code (e.g. \nAbout Lambda\n\n Founded in 2012, with 500+ employees, and growing fast\n \n\n Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove\n \n\n We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG\n \n\n Our values are publicly available: https://lambda.ai/careers\n