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We are looking for a deeply technical and storage-savvy architect to lead our efforts in defining, selecting, and, where needed, designing storage solutions for our AI and HPC cluster deployments. These deployments range from tightly integrated, in-house systems to complex enterprise-grade solutions that must meet demanding performance and security standards. This role operates at the intersection of performance engineering, vendor evaluation, and architecture design.
Job Responsibility:
Act as the technical lead in evaluating third-party storage solutions, analyzing vendor roadmaps, performance metrics, security/compliance features, and cost models.
Ensure storage solutions align with workload-specific requirements, including throughput, inference latency, encryption, and cloud-related controls.
Benchmark and characterize storage solutions from multiple angles—bandwidth, latency, IOPS, scaling behavior, and integration friction.
Drive the development of both lightweight internal storage configurations and more unconventional in-house storage solutions for targeted use cases, working directly with a small team of SW engineers.
Maintain deep expertise in low-level storage hardware - including media types (e.g., NVMe, SCM), device-level capabilities, and transport-layer technologies (e.g., NVMe-oF) - while tracking vendor roadmaps and emerging trends. Identify components that align with performance targets and map them to workload characteristics.
Collaborate across architecture and platform teams to ensure that storage designs meet security and compliance expectations for hyperscaler and enterprise environments.
Stay current on evolving customer expectations and align storage choices accordingly.
Interface with hardware, software, and deployment teams to validate that selected storage solutions integrate cleanly with system architecture and support operational goals.
Track and document storage variations across cluster generations and customer-specific deployments.
Requirements:
7+ years of experience in storage architecture, preferably in data-intensive environments such as AI/ML, HPC, or cloud-scale systems.
Deep understanding of file systems, including performance and scalability trade-offs, shared namespaces, and interfaces such as NFS, POSIX, and object-based ones like S3.
Strong understanding of modern storage technologies and protocols: NVMe, SCM, RAID, tiering, encryption, and distributed file systems.
Experience evaluating enterprise and cloud storage solutions against workload-driven performance and compliance targets.
Familiarity with system-level trade-offs involving IOPS, bandwidth, latency, durability, and cost.
Excellent communication skills and the ability to distill complex storage trade-offs into clear recommendations.
Nice to have:
Experience designing or deploying internal storage stacks for focused or non-traditional use cases.
Understanding of storage needs in containerized, multi-tenant, or hybrid environments.
Familiarity with benchmarking tools and methodologies for profiling storage behavior across diverse scenarios.
What we offer:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.