Software Engineer, Productivity - Networking

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, Reliability Engineering, Observability, Developer Productivity or Cloud Infrastructure. About the Role All teams are deeply collaborative, work on mission-critical services, and are responsible for building distributed, scalable infrastructure to bring OpenAI’s technology to the world through products like ChatGPT and the OpenAI API. You’ll work closely with stakeholders to understand infrastructure, data and compute needs, setting the technical strategy that supports cutting-edge research and product development. This is a critical role for someone who is passionate about solving complex engineering problems at scale, ensuring their performance, scalability and reliability Team Focus Areas Distributed Systems: Owning and building important, highly scalable, available, performant, and reliable distributed systems (and their building blocks) to power the entire stack at OpenAI Systems Engineering: Work across layers of the stack—debugging system bottlenecks, evolving core infrastructure, and solving novel problems in performance and scalability. Reliability Engineering: Build scalable, fault-tolerant systems and lead efforts around service health, incident response, and resilience. Observability: Design and maintain observability tooling (metrics, logs, tracing) to give teams visibility into production systems at scale. Developer Productivity: Create tools, environments, and workflows that help engineers ship high-quality software faster and more safely. Cloud Infrastructure: Own the cloud-native infrastructure (compute, networking, storage) that underpins all services and research workloads. Databases: Building high performance, distributed database systems that power all of OpenAI's product stack. In this

About the Team We’re hiring software engineers to make OpenAI’s Model Performance teams more productive. These teams work on the systems, tooling, and infrastructure that help improve model performance across OpenAI’s training and inference workloads at frontier scale. About the Role We’re looking for an autonomous, high-ownership developer productivity engineer who cares deeply about helping other engineers move faster, safer, and with more confidence. This role will sit within OpenAI’s Model Performance organization, contributing to developer infrastructure, CI systems, testing workflows, tooling, and broader performance infrastructure efforts. There is also a strong opportunity to contribute to the Triton project and help improve the systems that support performance-critical engineering work across OpenAI. In this role you will: Improve development workflows for engineers working on model performance infrastructure Design and improve CI/CD, release, validation, and testing pipelines Build and maintain tools that improve reliability, iteration speed, and engineering confidence Partner closely with engineers to identify friction in testing, debugging, deployment, and development workflows Contribute to infrastructure efforts that support performance-critical training and inference systems Help improve developer experience across Python-heavy codebases and performance-oriented infrastructure Work in a high-context, ambiguous environment where ownership and good judgment matter You might thrive in this role if: You are motivated by enabling the people around you and helping engineers do their best work You have strong experience with CI/CD, developer infrastructure, testing systems, tooling, or build/release workflows You are highly collaborative, empathetic, and comfortable partnering deeply with technical teams You are strong in Python and enjoy building reliable, scalable developer tools and infrastructure You have experience improving large-scale engineering work

About the Team We’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads. We’re hiring a Developer Productivity Engineer to help scale the engineering systems, safeguards, and developer workflows that enable our teams to move quickly without compromising reliability or performance. This role sits at the intersection of developer experience, CI/CD infrastructure, release engineering, production readiness, and inference systems reliability. You’ll work on the tooling and operational foundations that support model launches, inference optimizations, cloud provider integrations, and large-scale deployments across a rapidly evolving inference stack. About the Role We’re looking for an autonomous, high-ownership engineer who cares deeply about making other engineers faster, safer, and more confident. A major focus of this role will be improving the tooling and infrastructure around deploy gates for inference engine images. These systems help ensure that every image released to production and research is correct, numerically sound, free of regressions, and performant across key metrics like time-to-first-token (TTFT) and time-between-tokens (TBT). You’ll help harden the systems that catch issues before they reach production, reduce noise from flaky or infrastructure-related test failures, and improve automation around triage, ownership, debugging, and escalation when failures occur. You’ll also work on improving observability, rollout safety, release automation, and developer self-service tooling across a rapidly evolving inference stack. This is not generic internal tools work. The systems you build directly impact OpenAI’s ability to support new model launches, safely ship inference optimizations to the world, onboard new infrastructure providers, and operate one of the largest and most p

About the Team We’re hiring software engineers to make the Workload team more productive. The Workload team maintains the core components of OpenAI’s training and inference frameworks and helps execute frontier experiments. About the Role We’re looking for someone who cares about the developer experience of working in and around OpenAI’s core training and inference frameworks. In this role you will: Be responsible for optimizing the development workflows of the engineers around you Work within various Workload teams to address their specific needs, but collaborate with the centralized teams that own various aspects of development experience Optimize iteration speed, both broadly, and in particular by optimizing specific teams’ CI Improve reliability, for instance, by driving testing strategy for particular components Work through the long tail of things that it takes to build libraries and systems that will delight researchers You might thrive in this role if: You are motivated by helping people. You believe a thing that separates great teams from good teams are the players willing to do whatever work it takes, without ego. You believe in the power of developer experience. Something magical happens when people can quickly and confidently iterate on a simple codebase, but this magic is fragile and must be fought for. When you see someone trip over something, no matter how small, your first instinct is asking yourself what it would take for that to not happen again. Your second instinct is clicking merge on the PR you’ve already written to make it so. You are pragmatic. You have the ability to see the world through a perfectionist’s eyes, but are not yourself a perfectionist. You know which problems to pick and when to switch to making progress on a different problem. You like going end-to-end on things. You love co-design — that feeling when you were only able to find the right solution because you both deeply understand the users that interact with a system and the

About the Team The Applied AI team safely brings OpenAI's technology to the world. We released ChatGPT, Plugins, DALL·E, and the APIs for GPT-4, GPT-3, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. We serve end-users directly through ChatGPT, and serve developers through our APIs, which power product features that were never before possible. About the Role The Engineering Acceleration team designs, builds and maintains the foundational systems that engineers use to build ChatGPT and the API. This is a fast-growing team and you will get a chance to own and define the strategy, vision, and plan for how to increase developer productivity. In this role, you will: Drive the design, development, and implementation of tools, systems, and processes that accelerate engineering velocity, reduce manual effort, and increase the quality of output. Use our latest AI tools to re-think how we can be the most productive team in the industry. Work closely with various teams within OpenAI to understand their workflows, challenges, and needs, and ensure the tools and systems built by the Engineering Acceleration team address these requirements. Bring new features and research capabilities to the world by partnering with product engineers to lay the necessary technical foundations. Guide and advise product engineering teams on best practices for ensuring observable, scalable systems. Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years of experience in engineering, including 3+ years of experience in infrastructure building tooling for developers. Have experi

About the Team OpenAI’s Application Engineering team builds the internal products and platforms that help OpenAI operate securely and at scale. We engineer, own, and evolve OpenAI’s core productivity ecosystem, creating secure applications, integrations, automation, and reusable tooling where off-the-shelf software is not enough. Our work spans employee-facing experiences and the services, APIs, control planes, and governance that make them reliable, permission-aware, and scalable. We also act as a customer zero for OpenAI’s technology, building the enterprise foundations that let employees and agents safely access the context, tools, and actions they need. We partner closely with IT, Security, product teams, and platform providers to turn company-wide problems into durable systems, learn from real internal workflows, and help shape the products we deploy. We create paved paths that let teams move quickly without compromising security or operational quality. About the Role As a Staff Software Engineer on Agent Productivity, you will shape the foundation that enables teams to build agents with secure access to the context and capabilities they need. Slack will be the first and deepest implementation surface—and where you spend most of your time—owning its application architecture, integrations, APIs, governance, and administration automation while building patterns that extend to internal systems, identity platforms, and other enterprise applications. This is a hands-on engineering role with broad organizational impact as agents support more employee workflows. You will define platform architecture, build reusable foundations, and establish secure patterns for identity, permissions, connectivity, and operations that make agents easier to develop, deploy, and manage. In this role, you will: Own the technical strategy and architecture that enable teams to build, connect, and deploy agents quickly and safely, using Slack as the primary implementation surface. Design and