Infrastructure Engineering with AI Coding Tools

If you’re an infrastructure or security engineer, now is the best time to join OpenAI. It’s hard not to be inspired by what today’s coding tools are capable of, and we have line of sight to making them much better. While our core ML infrastructure problems remain much the same as always — training and inferencing models at scale, co-designing end-to-end for maximum effect, managing complexity and maintaining fast iteration — what it feels like to solve these problems in practice is changing fast. As the models have been improving, our ability to get value out of them is increasingly bottlenecked by thoughtfully designed infrastructure — whether figuring out how to manage agent cross-collaboration, having ergonomic sandboxes that let the agents complete end-to-end workflows securely, building tools/abstractions/observability/frameworks which allow the agents to move faster, and scaling supervision of the agents' work. Engineering is already different from a few months ago, and will continue to evolve. Having seen many generations of engineering and AI tools, I believe what is most important going forward will be skills like the following: strong understanding of your domain, ability to think through abstraction/architecture/design/how the pieces should fit together, and deep curiosity to explore what these models have to offer. If you’d like to help us build the future of AI, while using AI to get there, email me: [email protected]. Include a description of a surprising or creative way you’ve gotten value out of the models recently, and your contributions to any project in your career on which you’ve made a significant difference in its outcome. Feel free to include any other context that can help us understand how you operate and the problems you want to work on.