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Software Engineer, Compute Foundations

OpenAI · San Francisco

remoteunknown$255,000–$490,000Posted Sep 16, 2026KubernetesDistributed SystemsGoPythonLinuxAPIsInfrastructure as Code

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About this role

**Software Engineer, Compute Foundations** **ABOUT THE TEAM** Compute Foundations builds software managing OpenAI's GPU compute infrastructure across sites and data centers. We create Kubernetes-based control planes, controllers, services, and APIs coordinating machine and cluster lifecycles. **ABOUT THE ROLE** Build distributed systems provisioning, configuring, and managing compute throughout its lifecycle. Connect global services with bare-metal systems, designing lifecycle APIs, improving controller performance, and tracing provisioning failures across the stack. **KEY RESPONSIBILITIES** • Design and operate Kubernetes controllers and distributed services coordinating infrastructure across sites • Define APIs and resource models for lifecycle operations across hardware platforms • Build provisioning and configuration services coordinating network boot, hardware management, and deployment • Develop lifecycle management for discovery, allocation, provisioning, upgrades, and recovery • Design reliable reconciliation and recovery through concurrent changes and partial failures • Improve control-plane throughput, API latency, and infrastructure state convergence • Integrate new sites and GPU hardware generations into the platform **IDEAL CANDIDATE** • Strong software engineering fundamentals with production distributed systems experience • Experience with Kubernetes APIs and reconciliation patterns • Understanding of bare-metal provisioning (PXE, DHCP/DNS, BMCs, firmware, Linux, drivers, configuration management) • Can design reliable APIs and asynchronous workflows with strong concurrency reasoning • Diagnoses reliability and performance problems across service and machine boundaries • Communicates effectively across engineering specialties **BONUS** • Built infrastructure control planes across multiple sites/regions • GPU or HPC infrastructure experience • Integrated multiple hardware platforms into a common service model

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