Software Engineer, Infrastructure Reliability

Software Engineer, Infrastructure Reliability About the Team We’re hiring software engineers to join our broader Infrastructure organization, which supports multiple high-impact teams. Depending on your interests and experience, you could work on one of several focus areas—including Core Distributed Systems, Databases, Observability, or Cloud Infrastructure. All teams operate with a high degree of autonomy and are deeply collaborative, with a shared mandate to raise the bar on safety, reliability, and velocity across OpenAI. About the Role You’ll be at the heart of scaling and hardening the infrastructure that powers some of the most widely used AI systems in the world. You’ll help ensure our systems are highly reliable, observable, performant, and secure—so researchers can iterate quickly, and products like ChatGPT and the OpenAI API can serve millions of users safely and effectively. This is a hands-on, high-leverage role for engineers who thrive on ownership, love solving deep technical problems across the stack, and want to work on systems that support cutting-edge research and deploy at global scale. You’ll play a key part in shaping technical direction, proactively improving system resilience, and collaborating closely with infra, product, and research teams to turn complex infrastructure into reliable platforms. In this role you will: - Design, build, and operate reliable and performant systems used across engineering. - Identify and fix performance bottlenecks and inefficiencies, ensuring our infrastructure can scale to the next order of magnitude. - Dig deep to resolve complex issues. - Continuously improve automation to reduce manual work. Improve internal tooling and our developer experience. - Contribute to incident response, postmortems, and the development of best practices around system reliability and scalability. You might thrive in this role if you: - Have a deep understanding of distributed systems principles and a proven track record in building and operating scalable and reliable systems. - Have a keen eye for performance and optimization. You know how to squeeze the most performance out of complex, globally-distributed systems. - Have experience operating orchestration systems such as Kubernetes at scale and building abstractions over cloud platforms - Are comfortable working in Linux environments, and with tools like Kubernetes, Terraform, CI/CD pipelines, and modern observability stacks. - Are experienced in collaborating with cross-functional teams to ensure that reliability and scalability are considered in the design and development of new features and services. - Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. - Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. - Are comfortable with ambiguity and rapid change. Qualifications: - 4+ years of relevant industry experience, with 2+ years leading large scale, complex projects or teams as an engineer or tech lead - A passion for distributed systems at scale with a focus on reliability, scalability, security, and continuous improvement. - Proven experience as an reliability engineer, production engineer, or a similar role in a fast-paced, rapidly scaling company. - Strong proficiency in cloud infrastructure (like AWS, GCP, Azure) and IaC tools such as Terraform. Proficiency in programming / scripting languages. - Experience with containerization technologies and container orchestration platforms like Kubernetes. - Experience with observability tools such as Datadog, Prometheus, Grafana, Splunk and ELK stack. - Experience with microservices architecture and service mesh technologies. - Knowledge of security best practices in cloud environments. - Strong understanding of distributed systems, networking, and database technologies. - Excellent problem-solving skills and ability to work in a fast-pa ... (truncated, view full listing at source)