Aws in United States

About the Team The Scaling team is responsible for the architectural and engineering backbone of OpenAI’s infrastructure. We design and deliver advanced systems that support the deployment and operation of cutting-edge AI models. Our work spans system software, networking, platform architecture, fleet-level monitoring, and performance optimization. About the Role We’re hiring an SW Engineer to enable production workloads and end-to-end testing on new platforms. This role will include creating new test harnesses and platform stress benchmarks, porting existing inference and training workloads to new, sometimes early-access, systems/hardware, analyzing performance and bottlenecks, and characterizing the end-to-end behavior of new systems (compute, comms, storage, control plane, and failure modes). Key Responsibilities Port and validate key inference and training workloads on new platforms/SKUs as they arrive; drive correctness, performance, and stability to an internal readiness bar. Build a suite of benchmarks and stress tests that capture real E2E behavior of our workloads by exercising all aspects of a system, including CPU, GPU, memory subsystem, frontend, scale-up, and scale-out networking (including WAN traffic, NVlink and RDMA collectives), storage, thermals, and any other relevant parts. Deep-dive performance on distributed training/inference: Collective performance and tuning (across NCCL/RCCL and internal libraries) Overlap of compute/communication, kernel-level bottlenecks, memory bandwidth and scheduling effects Create repeatable test harnesses that run in CI / lab environments and produce actionable outputs (pass/fail, performance score, regression detection). Partner with systems + fleet bring-up engineers to ensure the platform is not only stable and performant, but also operationally usable and scalable (containerization, K8s integration, telemetry hooks, failure triage loops). Work cross-functionally with vendors and internal stakeholders by producing

About the Role As a Director, Compute & Infrastructure FP&A, you will own and drive the monthly forecasting process for the Compute & Infrastructure org by partnering with various stakeholders across Finance, Accounting, Tax and Engineering. You will play a critical role in planning and forecasting the company’s largest and most complex cost center ( Compute & Infrastructure ). You will collaborate cross-functionally to develop long-range infrastructure investment plans, evaluate build vs. buy decisions, and ensure capital is deployed efficiently to support rapid growth. You will also provide strategic financial guidance through scenario modeling, ROI analysis, and performance tracking, enabling leadership to make high-stakes decisions under uncertainty. What You’ll Do Own compute financial planning & Forecasting. Build and manage consolidation models for GPU/CPU capacity, storage, networking, and data center investments. Translate infrastructure roadmaps into short- and long-term financial forecasts (LRP, annual planning) Coordinate closely with Corporate FP&A on timelines and process Present insights on a monthly basis to senior management. Drive infrastructure investment decisions. Evaluate build vs. buy, vendor vs. owned infrastructure, and capacity allocation tradeoffs. Develop frameworks for investment trade-offs to guide executive decision making. Build scalable tooling & reporting. Implement stakeholder-facing dashboards to track compute spend, utilization, and efficiency metrics. Improve visibility into unit economics (e.g., cost per training run, cost per inference, cost per customer). Drive forecasting accuracy & accountability. Lead budget vs. actual analysis for compute and infrastructure spend. Identify key cost drivers (utilization, pricing, efficiency gains) and reduce forecast variance. Support close & financial reporting. Partner with Accounting to ensure accurate classification of infrastructure spend (OpEx vs C

About the Team The Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products. Our systems help teams ship safely, evaluate product and model changes in production, and make high-confidence decisions from real-world usage. Statsig began as an independent company built around experimentation, feature management, and product analytics at scale. After Statsig joined OpenAI, the team began the next chapter: bringing that platform expertise and infrastructure into OpenAI as the experimentation and rollout foundation for every product we ship. This is infrastructure with a very direct product consequence. Teams working on ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and shared platform systems depend on Statsig to evaluate configurations, move traffic safely, ingest experiment data, serve analytics, and roll changes forward or back when production reality demands it. We are at a critical point in the platform journey. Adoption is accelerating quickly across OpenAI, and the systems that were already important are becoming load-bearing for how the company launches. The infrastructure needs to stay fast under sharply increasing evaluation volume, reliable when more services depend on it, observable enough to debug quickly, and efficient enough to support OpenAI-wide scale. Recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency across important services. The next phase is to make those gains systematic: a platform that can absorb rapidly growing product velocity while preserving low latency, data quality, operational safety, and developer trust. Based out of OpenAI's Bellevue office, we are a close-knit team that values in-person collaboration, technical depth, operational ownership, and building infrastructure that

About the Team The GPT Infrastructure team builds systems that turn advances in model inference and optimization into reliable production capabilities. We enable OpenAI workloads to be qualified and optimized across new accelerator platforms without requiring a one-off port and tuning effort for every hardware target. Our work spans distributed systems, model execution, compilers and runtimes, performance engineering, secure partner integrations, evaluation systems, and developer tooling. We build the infrastructure that makes optimization workflows automated, reproducible, and trustworthy. About the Role We are seeking a software engineer to help build the platform that qualifies and optimizes inference workloads across heterogeneous compute environments. You will develop both OpenAI-hosted services and secure partner-side software for running long-lived optimization workflows. These workflows generate candidate kernels, runtime configurations, and serving-stack changes; compile and execute them on target hardware; verify their correctness; measure their performance; and use the results to guide further optimization. You will work across model architecture, distributed execution, compilers, runtimes, networking, and accelerator systems. A central part of the role is turning research prototypes and one-off hardware bring-up efforts into reliable, reusable infrastructure with clear contracts, reproducible results, strong observability, and well-defined security boundaries. Key Responsibilities Design, build, and operate APIs and control-plane services for long-running workload qualification and optimization campaigns, including scheduling, retries, checkpointing, resource budgets, and observability. Build secure partner-side execution and evaluation software that can compile, run, verify, profile, and benchmark candidate artifacts on accelerator hardware. Integrate model workloads, hardware profiles, compiler toolchains, runtimes, serving engines, and distributed-exe

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 Role The Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production. We own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across OpenAI to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous. This role sits at the intersection of developer productivity, distributed systems reliability, and large-scale infrastructure orchestration. In This Role, You Will Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback. Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows. Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale. Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns. Build systems that automatically evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger safe rollbacks. Build systems that support agent-assisted or autonomous deployment workflows using modern AI tooling. Technologies commonly used in this environment include: Kubernetes for large-scale container orchestration and runtime infrastructure Python and FastAPI for internal services Terraform for infrastructure as code GitOps-based deployment workflows (e.g., ArgoCD, Flux, or similar systems) Buildkite for CI orchestration You may be a strong fit if you: Have worked with Kubernetes-based deployment systems at scale Have experience building or operating continuous deployment platforms Are familiar with GitOps tooling such as

About the Team The Strategic Finance team provides financial insights and guidance to support OpenAI’s long-term goals and strategies. We partner across the business to allocate and deploy our resources for the highest-impact outcomes.  Within Strategic Finance, the B2B team focuses on the financial performance of our products and GTM functions, ensuring tight alignment between financial objectives and company strategy. We partner with leaders across Product, GTM, Research, Partnerships, and Operations to: Drive operational planning, financial forecasting, and performance management. Provide decision-quality insights on product and financial performance to inform strategic resource allocation. Build the “0→1” financial foundations required to scale and accelerate growth. About the Role We are hiring a senior leader in B2B Strategic Finance to build and scale a new pillar within our finance organization. This is a highly visible role that reports into the Head of B2B Strategic Finance and supports some of our most critical executive stakeholders, including our COO, CFO, and CRO, among others on the B2B Leadership Team. This role is ideally based in our San Francisco HQ, but we are open to NYC and Seattle. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Drive B2B finance scale and rigor Build and scale core financial infrastructure across the B2B business, including forecasting methodology, variance management, and performance narratives that drive accountability and decision-making velocity. Lead consolidated planning across revenue, gross margin (including compute), and opex for annual budget, forecasts, regular business reviews, and long-range planning. Establish durable management reporting: KPI definitions, dashboards, month-end/quarter-end deliverables, and exec-ready readouts. Partner with Corporate FP&A, Accounting, and Finance Systems/Data to evolve processes and contro

About the Team The Premium team owns some of the highest-leverage customer-facing levers in ChatGPT’s consumer revenue business, spanning the paid customer journey: helping users understand the value of paid plans, convert with confidence, and continue finding lasting value in their subscription. Our work is highly cross-functional, partnering with Product, Data Science, Design, FinEng, Finance, Legal, Support, and Marketing to improve free-to-paid conversion, renewal, customer lifetime value, and revenue while keeping the experience trustworthy, scalable, and low-friction. In This Role, You Will: Lead and scale an engineering team responsible for some of ChatGPT’s most important subscription and monetization experiences. Own the technical execution for Premium customer experiences across plan merchandising, paywalls, upgrade flows, checkout UX, plan management, renewals, downgrades, and cancellation. Partner with Product and Data Science to run high-quality experiments across upgrade, trial, renewal, downgrade, and cancellation flows. Improve key subscription metrics including conversion, renewal, churn, ARPU, and lifetime value. Build reliable customer-facing Premium experiences for purchase, plan management, renewal, downgrade, cancellation, and access-related states at scale. Partner closely with FinEng and other platform teams to evolve the billing, payments, and entitlement capabilities that power Premium experiences. Collaborate closely with Product, Design, Data Science, Finance, Legal, Support, and Marketing on monetization strategy and execution. You Might Thrive in This Role If You: Have 5+ years of engineering management experience, Have strong technical expertise in backend, frontend, or full-stack development, with experience building growth-oriented features. Have a track record of improving conversion, retention, or monetization through experimentation and data-driven product engineering. Are experienced with subscription products, plan merchandising

About the team OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Sales team partners closely with customers to deeply understand their businesses and needs, helping inform the development of products and solutions that drive meaningful revenue growth and long-term success on the platform—while maintaining strong standards for user trust and platform integrity. About the role We’re looking for an Account Manager to support advertisers in onboarding, launching, and growing on OpenAI’s advertising platform. You will manage a portfolio of partners and serve as a trusted advisor, helping them achieve their business objectives while ensuring a strong and responsible experience on our platform. This role sits at the intersection of relationship management, strategy, and execution. You’ll work closely with Sales to drive long-term partner growth and with internal teams to continuously improve the advertiser experience. In this role, you will: Own relationships with a portfolio of advertising partners, serving as their primary point of contact. Guide advertisers through onboarding and campaign launches to ensure strong adoption of OpenAI’s ads products. Analyze campaign performance and provide clear, actionable recommendations to improve outcomes. Identify opportunities to expand partnerships through increased product adoption and incremental investment. Partner cross-functionally with Sales, Product, Analytics, Policy, and Operations to resolve issues and enhance platform value. Surface advertiser feedback and insights to inform product improvements and long-term strategy. Help build scalable processes and best practices that support the growth of OpenAI’s advertising ecosystem. You might thrive in this role if you: Has 5-10+ years of experience in digital advertising, account management, customer success, consulting or a related client-facing role. Has experience managing advertiser or agency r

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users. What You’ll Do Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows. Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases. Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation. Analyze failures in production and systematically improve robustness and reliability. Build feedback loops and data systems that get better real-task data into evaluation and research. Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on. Help define what “good” looks like for agents completing complex tasks end-to-end. You Might Be a Good Fit If You Ha

About the Team We’re hiring software engineers to make OpenAI’s networking teams more productive. These teams build and operate the high-performance networking systems that support OpenAI’s training and inference infrastructure at frontier scale. About the Role We’re looking for someone who cares deeply about the developer experience of engineers working on complex infrastructure systems — especially around build systems, test architecture, release pipelines, and reliable development workflows. This role will be embedded with OpenAI’s networking team: making it faster, safer, and easier for engineers to build, test, validate, and ship changes across multi-server, networked, and hardware-adjacent environments. In this role you will: Improve development workflows for engineers building and operating OpenAI’s networking systems Design and improve continuous deployment, release, and validation pipelines Build and maintain test harnesses for multi-server, networked, and hardware-backed environments Improve iteration speed across C++, Python, and build-system-heavy codebases Partner with engineers to identify friction in CI, testing, debugging, and deployment workflows Drive testing and reliability strategy for infrastructure components that support large-scale training and inference workloads Work closely with centralized developer experience teams while staying deeply embedded with the networking engineers closest to the systems You might thrive in this role if: You are motivated by helping other engineers move faster and with more confidence You have experience with CI/CD, release pipelines, testing infrastructure, or build systems You are comfortable moving between C++, Python, and build systems such as CMake, Bazel, or Blaze You enjoy building test harnesses, automation, and workflow improvements for complex systems You do not need to be a networking expert, but you are excited to learn enough about the domain to make the team meaningfully more effective When you see

About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After Statsig joined OpenAI, the team began the next chapter: bringing that deep product expertise, customer intuition, and mature platform infrastructure into OpenAI as the experimentation and rollout platform for every product we ship. Today, we support teams across ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and the shared infrastructure that connects them. These teams rely on Statsig to safely introduce new capabilities, compare product and model behavior, measure impact, and roll changes forward or back with confidence. We are at a defining moment in the platform journey. OpenAI has the data, product surface area, and pace of innovation to learn faster than almost any organization in the world, but that potential only becomes real if teams can experiment responsibly, measure clearly, and roll out changes safely. Adoption of the platform is accelerating rapidly across the company, and recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency for important services. Based out of OpenAI’s Bellevue office, we are a close-knit team that values in-person collaboration, urgency, craft, and impact. We build for other builders, and the best version of this team is one where every OpenAI product team can move faster because the experimentation and rollout layer is dependable, fast, and easy to use. About the Role We are l

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About Us: Notion helps you build beautiful tools for your life’s work. In today's world of endless apps and tabs, Notion provides one place for teams to get everything done, seamlessly connecting docs, notes, projects, calendar, and email—with AI built in to find answers and automate work. Millions of users, from individuals to large organizations like Toyota, Figma, and OpenAI, love Notion for its flexibility and choose it because it helps them save time and money. In-person collaboration is essential to Notion's culture. We require all team members to work from our offices on Mondays, Tuesdays, and Thursdays, our designated Anchor Days. Certain teams or positions may require additional in-office workdays. About the Role: Millions of people rely on Notion to do their most important work. Protecting that trust starts with protecting the people who build Notion: our employees, their laptops, their identities, and the SaaS apps they rely on every day. We are looking for a hands-on Corporate Security Engineer to own and improve the technical controls that keep our workforce and corporate environment safe. This is a security engineering

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. About Fern, a Postman Company Fern helps software companies build a world-class API experience. Our customers include industry leaders like Nvidia, Square, and Twilio, as well as fast-growing AI companies like ElevenLabs and OpenRouter. In the next year, the majority of API integrations will be implemented by AI agents. Agents don’t read marketing pages. They need strongly typed schemas, structured endpoints, deterministic contracts, and documentation that can be fed into a context window. Our team is small and talent-dense. We’re a team of builders from Google, Palantir, Amazon, and Uber, working together in New York City. About the Role As a Senior Software Engineer at Fern, you’ll build APIs, scale AI infrastructure, and design developer experiences that reach millions of people. Scale infrastructure to keep up with growth: Work on AI systems deployed on Vercel, AWS, and Turbopuffer that must be performant, reliable, and secure under real-world load. Stay close to customers: We work directly with API teams at companies like Nvidia, Twilio, and Square. You’ll debug real production edge cases, shape APIs ba

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. About Fern, a Postman Company Fern helps software companies build a world-class API experience. Our customers include industry leaders like Nvidia, Square, and Twilio, as well as fast-growing AI companies like ElevenLabs and OpenRouter. In the next year, the majority of API integrations will be implemented by AI agents. Agents don’t read marketing pages. They need strongly typed schemas, structured endpoints, deterministic contracts, and documentation that can be fed into a context window. Our team is small and talent-dense. We’re a team of builders from Google, Palantir, Amazon, and Uber, working together in New York City. About the Role As a Staff Software Engineer at Fern, you’ll build APIs, scale AI infrastructure, and design developer experiences that reach millions of people. Set technical direction: Drive system design decisions around data modeling, performance, correctness, and reliability. Identify scaling bottlenecks before they become problems. Build for durability and scale: Ensure our systems are performant, observable, secure, and resilient under real-world production load across infrastructur