Software Engineer, Compute Foundations

Design, build, and operate Kubernetes-based controllers and distributed services that coordinate infrastructure across sites, isolate failures, and scale as GPU capacity grows.

Define APIs and resource models that let clients request and track lifecycle operations through consistent interfaces across hardware platforms and providers.

Build provisioning and configuration services that coordinate network boot, hardware management interfaces, and the deployment of firmware, operating-system images, drivers, and host configuration.

Develop lifecycle management for discovery, allocation, provisioning, upgrades, maintenance, recovery, and decommissioning, integrating with health and validation systems.

Design reliable reconciliation and recovery through concurrent changes, interrupted operations, and partial failures, with staged rollouts that limit disruption across nodes, racks, and clusters.

Improve control-plane throughput, API latency, and the time infrastructure takes to reach its desired state, while respecting the limits of site systems and provider APIs.

Build the software integrations that bring new sites and GPU hardware generations into the platform, partnering with hardware, networking, data-center, and other infrastructure teams.

Have strong software engineering fundamentals and experience designing, implementing, and owning production distributed systems or infrastructure services.

Have experience developing infrastructure systems that use Kubernetes APIs and reconciliation to manage resources.

Understand how a bare-metal node moves from power-on to a configured, workload-ready system, with depth in one or more areas such as PXE, DHCP/DNS, baseboard management controllers (BMCs), firmware, Linux, drivers, images, or configuration management.

Can design reliable APIs and asynchronous workflows, reasoning about concurrency, consistency, idempotency, and failures across service and provider boundaries.

Can diagnose reliability and performance problems across service, operating-system, and machine boundaries, turning production evidence into lasting software improvements.

Work effectively across engineering specialties and communicate system behavior and technical tradeoffs clearly.

Have built infrastructure control planes that coordinate operations across multiple sites or regions.

Have worked with GPU or HPC infrastructure, including topology and shared dependencies across machines, racks, or clusters.

Have integrated multiple hardware platforms or infrastructure providers into a common service or resource model.

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 capabilities of AI systems and seek to safely deploy them to the world through our products.

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 capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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