OpenAI· Hardware· San Francisco
Systems Engineer (Network / Storage / Systems)
Comp$335K – $455K
Classified Tasks (16)
Automate 0%Augment 63%Human-Only 38%
Augment (10)
AI assists, human decides
Architect core infrastructure systems that enable Stargate deployments
technical
Validate core infrastructure systems through testing and verification procedures
technical
Operationalize core infrastructure systems for production use across deployments
operational
Design and improve top-of-network architectures spanning frontend, WAN, OOB, firewall, and adjacent infrastructure layers
technical
Drive logical network readiness including routing configuration, configuration management, provisioning, and issue resolution
operational
Define storage architectures across in-rack, in-pod, cluster, and cloud tiers with emphasis on performance, lifecycle, and cost efficiency
technical
Evaluate vendor hardware and infrastructure proposals and provide technical feedback on architecture, reliability, and operational fit
analytical
Build tools and automation to improve lab operations, SKU onboarding, fleet readiness, and deployment velocity
technical
Establish repeatable engineering standards, operational processes, and readiness gates for Stargate expansions
leadership
Design and deliver next-generation compute environments that support large-scale model training and inference
technical
Human-Only (6)
Requires human judgment
Own system engineering workstreams across domains including networking, storage, system validation, and bring-up
leadership
Lead system bring-up for new hardware platforms including imaging, provisioning, validation, and readiness for production deployment
operational
Debug complex system faults across firmware, NIC, GPU, server, and platform layers and drive cross-functional root cause analysis with internal teams and external vendors
technical
Partner with hardware engineering, cluster software, and infrastructure operations to translate new compute platforms into stable production environments
communication
Coordinate cross-functional efforts across networking, storage, system bring-up, hardware debugging, and cluster readiness
leadership
Build physical and logical infrastructure components required to power large-scale AI systems
technical
Job description
Systems Engineer (Network / Storage / Systems) | OpenAI Careers ## Systems Engineer (Network / Storage / Systems) Hardware - San Francisco Apply now(opens in a new window) **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 acros