OpenAI· Scaling· San Francisco and Seattle
Software Engineer, System Enablement
Comp$293K – $455K
Classified Tasks (32)
Automate 0%Augment 63%Human-Only 38%
Augment (20)
AI assists, human decides
Design and deliver advanced systems that support the deployment and operation of AI models
technical
Build images for new systems (image build)
technical
Create user-data and configuration for nodes
technical
Join nodes to the appropriate Kubernetes control plane
technical
Implement and enforce readiness gates for new nodes
technical
Build and maintain golden image and provisioning workflows across lab and production environments
technical
Work with partner-provided base images and reconcile OS/version requirements
technical
Integrate nodes into fleet infrastructure and Infrastructure-as-Code pipelines (e.g., Terraform, Chef) with partner teams
technical
Ensure cloud resources map cleanly onto internal lifecycle expectations (e.g., VMSS/instance pools, image references)
operational
Define and manage pool definitions, network/WAN connectivity and routing, and admission controls for scheduling integration
technical
Modify scheduling integration when new SKUs require changes
technical
Drive registration and inventory correctness for systems that track nodes and their metadata
operational
Collaborate with partner teams to implement baseline health and telemetry bring-up
communication
Define minimum viable health signals for new hardware
analytical
Implement pass/fail checks for node health
technical
Implement automated reporting suitable for early ramp decisions
analytical
Debug kubelet and control-plane connectivity issues
technical
Debug storage constraints
technical
Make new systems observable by implementing appropriate telemetry and monitoring
technical
Work across lab and cloud provider integration for provisioning and fleet/cluster management
operational
Human-Only (12)
Requires human judgment
Own the end-to-end bring-up and bootstrap path for new systems and compute nodes from bare metal/early access to schedulable fleet capacity
operational
Partner with scheduling and platform owners to ensure new hardware is reachable and schedulable
communication
Provide hands-on support to register nodes and make them visible end-to-end
operational
Debug PXE and boot-loader issues
technical
Debug UEFI and BIOS issues
technical
Debug BMC issues
technical
Debug OS bring-up issues
technical
Debug NIC and network reachability issues
technical
Debug early rack and lab setup realities
operational
Bootstrap pre-production hardware into operational state
operational
Stabilize early hardware platforms into stable fleet capacity
operational
Turn new SKUs into capacity usable by internal customers
operational
Job description
Software Engineer, System Enablement | OpenAI Careers ## Software Engineer, System Enablement Scaling - San Francisco and Seattle Apply now(opens in a new window) **About the Team** The Scaling team is responsible for the architectural and engineering backbone of OpenAI’s infrastructure. We design and deliver advanced systems that support the deployment and operation of cutting-edge AI models. Our work spans system software, networking, platform architecture, fleet-level monitoring, and performance optimization. **About the Role** We’re looking for an engineer who can take early, sometimes messy, pre-production hardware and make it “real”: bootstrapped, stable, imaged, joined to the right Kubernetes control plane, registered correctly, scheduled, and observable. You’ll sit at the intersection of early HW bring-up, provisioning automation, fleet/cluster management systems, and lab or cloud provider integration—turning new SKUs into capacity that is usable by internal customers. **Key Responsibilities** * Own the end-to-end bring-up and bootstrap path for new systems and compute nodes from *bare metal/early access in lab or production/cloud environments* to *schedulable fleet capacity*: image build, user-data/config, cluster join, and readiness gates. * Build and maintain “first-class” golden image + provisioning workflows across lab, and production environments, including working with partner-provided base images and reconciling OS/version requirements. * Work with partner teams to integrate nodes into our fleet infrastructure and IaC pipelines (Terraform, Chef, etc.), ensuring cloud resources map cleanly onto our internal lifecycle expectations (e.g., VMSS/instance pools, image references). * Partner with scheduling and platform owners to ensure new hardware is reachable and scheduled (pool definitions, network/WAN connectivity/routing, admission controls, platform-specific quirks), including cases where new SKUs require changes for scheduling integration. * Drive registration and inventory correctness (e.g., systems that track nodes and their metadata), including hands-on support to get nodes registered and visible end-to-end. * Collaborate with partner teams to implement baseline health + telemetry bring-up: minimum viable health signals, pass/fail checks, and automated reporting suitable for early ramp decisions * Debug issues across layers: PXE/boot-loader, UEFI/BIOS, BMC, OS bring-up, NIC/network reachability, kubelet/control-plane connectivity, storage constraints, and early rack/lab realities. **Qualifications** * BS in CS/EE (or equivalent practical experience). * 5+ years of experience in systems SW development and building/operating Linux-based infrastructure in production or pre-production environments. * Strong, hands-on experience with: + Kubernetes cluster operations (node lifecycle, bootstrap/join, debugging control-plane connectivity) + Infrastructure-as-Code / config management (Terraform, Chef/Ansible, etc.) + Provisioning and imaging (PXE/iPXE, golden images, cloud-init/user-data) + Networking fundamentals (L2/L3, routing, DNS, fire-walling; comfort debugging reachability * Proven ability to write automation in Python/Go/Bash and ship operational tooling/run-books. **Preferred Skills** * Experience bringing up new hardware platforms (early silicon/servers/NICs) in a lab setting and turning them into stable fleet capacity. * Multi-cloud operational experience (Azure/GCP/AWS/OCI), especially with compute pools (e.g., VMSS / instance pools). * Experience building telemetry/health pipelines (agent-based metrics/logging, health rollups, readiness criteria). * Familiarity with WAN, peering, and multi-site network concepts for cluster deployments. **About OpenAI** OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabiliti