Software Engineer, Infrastructure - Analytics Platform

The Scaling team designs, builds, and operates critical infrastructure that enables research at OpenAI.

Our mission is simple: accelerate the progress of research towards AGI. We do this by building core systems that researchers rely on - ranging from low-level infrastructure components to research-facing custom applications. These systems must scale with the increasing complexity and size of our workloads, while remaining reliable and easy to use.

We're looking for an experienced software engineer to design, develop, and operate production-critical software infrastructure end to end across its full production lifecycle.

This role is centered on backend / systems engineering, with emphasis on low-level performance, scalability, distributed systems, and hands-on development and operation of critical services at scale. You'll take ambiguous problems, turn them into concrete plans, ship pragmatic solutions quickly, and improve them through production feedback and iteration.

This is not a general Python backend role. We're specifically looking for strong systems experience in Rust or C++, especially in performance-sensitive infrastructure.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

- Own critical infrastructure across design, implementation, rollout, operation, and iteration.

- Build and operate performant backend systems in Rust or C++ that support core research workflows.

- Design and improve distributed data and serving systems, including tradeoffs around partitioning, replication, consistency, retries, backpressure, and failure isolation.

- Debug real production bottlenecks across latency, throughput, contention, hot spots, and overload behavior.

- Operate business-critical services through on-call, incidents, postmortems, observability, alerting, safe rollouts, rollback plans, and zero-downtime migrations.

- Improve reliability of services running on Kubernetes, including resource tuning, failure handling, and production readiness.

- Partner closely with engineers and researchers to deliver fast, reliable, useful systems.

- Raise the bar through strong technical judgment, ownership, and follow-through.

- A track record of owning operationally critical systems end to end and delivering outcomes in ambiguous environments.

- Strong hands-on experience building performance-sensitive backend systems in Rust or C++.

- Comfort working below typical service abstractions, including concurrency, async execution, memory behavior, serialization, I/O, networking, profiling, and failure analysis.

- Experience designing, building, or operating distributed systems or distributed databases at meaningful scale.

- Preferably, experience with ClickHouse-like systems or infrastructure for analytics, telemetry, logging, search, ingestion, storage, or query execution.

- Hands-on experience with production infrastructure and delivery tooling, including Kubernetes, Terraform or equivalent infrastructure-as-code tooling, Prometheus or equivalent observability / metrics tooling, and CI/CD pipelines or equivalent release automation.

- Hands-on experience operating production-critical systems across the full lifecycle, including incidents, observability, alerting, safe rollouts, rollback plans, and recurrence prevention.

- Strong judgment in balancing engineering quality, speed, risk, and business impact.

- A habit of shipping practical first versions and improving them through production feedback.