Systems Engineer (Network / Storage / Systems)

OpenAI
San FranciscoPosted 25 April 2026

Job Description

Systems Engineer (Network / Storage / Systems) About the Team The Stargate team is responsible for building the physical and logical infrastructure that powers large-scale AI systems. We design and deliver next-generation compute environments that support frontier model training and inference across an expanding global footprint. This work spans hardware systems, networking, storage, cluster operations, and vendor ecosystems—turning aggressive compute growth plans into scalable, reliable production environments. About the Role We are seeking a System Engineer (Network / Storage / Systems) to help architect, validate, and operationalize the core infrastructure systems that enable Stargate deployments. In this role, you will work across networking, storage, system bring-up, hardware debugging, and cluster readiness. You will partner closely with hardware engineering, cluster software, infrastructure operations, and external vendors to ensure new systems are deployed efficiently and run reliably at scale. This role is ideal for engineers who can operate across hardware and software boundaries, solve ambiguous technical problems, and drive complex systems into production. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities - Own system engineering workstreams across one or more critical domains including networking, storage, system validation, or bring-up. - Design and improve top-of-network architectures spanning frontend, WAN, OOB, firewall, and adjacent infrastructure layers. - Drive logical network readiness including routing, configuration management, provisioning, and issue resolution. - Define storage architectures across in-rack, in-pod, cluster, and cloud tiers with focus on performance, lifecycle, and cost efficiency. - Evaluate vendor hardware and infrastructure proposals, providing technical feedback on architecture, reliability, and operational fit. - Lead system bring-up for new hardware platforms including imaging, provisioning, validation, and readiness for production deployment. - Debug complex system faults across firmware, NIC, GPU, server, and platform layers; drive root cause analysis with internal teams and external vendors. - Build tools and automation that improve lab operations, SKU onboarding, fleet readiness, and deployment velocity. - Partner with hardware, clusters, and operations teams to translate new compute platforms into stable production environments. - Establish repeatable engineering standards, operational processes, and readiness gates for future Stargate expansions. Qualifications - 7+ years of experience in systems engineering, infrastructure engineering, hardware platforms, or large-scale compute environments. - Strong technical depth in one or more areas: networking, storage systems, server platforms, firmware, Linux systems, or distributed infrastructure. - Experience bringing up new hardware systems or clusters in lab or production environments. - Experience debugging low-level hardware/software issues and driving cross-functional RCA efforts. - Familiarity with hyperscale infrastructure, AI clusters, HPC environments, or data center systems. - Experience working with OEM, ODM, JDM, or hardware vendors. - Strong scripting or software skills in Python, Go, Bash, or similar. - Ability to operate effectively in fast-moving environments with high ownership and evolving technical requirements. Preferred Skills - Experience supporting GPU clusters or accelerator-based infrastructure at scale. - Familiarity with cluster management, provisioning, or fleet lifecycle tooling. - Experience with network automation, storage optimization, or systems observability. - Background working across both hardware and software engineering organizations. - Experience scaling greenfield infrastructure deployments or rapid expansion programs. About OpenAI OpenAI is an AI research ... (truncated, view full listing at source)
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