Software Engineer Snowcommand Jobs

About the Team ChatGPT relies on a large and growing GPU fleet to serve inference workloads reliably and efficiently. Our team builds the software, tooling, and operational systems that help manage this fleet at scale. We work across production engineering, distributed systems, capacity management, and operational automation to improve reliability, reduce manual work, and make better use of available compute. About the Role We are looking for a software engineer with experience building or operating large-scale production systems. You will develop the systems that help manage the GPU fleet powering ChatGPT, including tooling for fleet health, capacity planning, operational automation, and incident response. You will work closely with infrastructure, research, and product engineering teams to improve reliability, developer productivity, and compute utilization. This role is a good fit for engineers who enjoy solving complex operational problems and building software that makes production infrastructure easier to run at scale. In This Role, You Will Build software and internal tools to manage large-scale GPU infrastructure supporting ChatGPT inference. Develop systems for capacity planning, fleet health monitoring, and resource utilization. Automate operational workflows, including incident detection, diagnosis, and response. Identify and address bottlenecks affecting fleet reliability, scalability, and performance. Partner with infrastructure, research, and product engineering teams to improve the compute platform. You Might Thrive in This Role If You Have experience operating large-scale production infrastructure, GPU clusters, or other compute-intensive distributed systems. Have a background in production engineering, site reliability engineering, infrastructure engineering, or platform engineering. Have built software that automates operational workflows and reduces manual work. Have worked with distributed infrastructure, cluster orchestration, or large-scale int

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Software Engineer to join our Data Acquisition team. Responsibilities: Own and lead engineering projects in the area of data acquisition including web crawling, data ingestion, and search. Collaborate with other sub-teams, such as Data Processing, Architecture, and Scaling, to ensure smooth data flow and system operability. Work closely with the legal team to handle any compliance or data privacy-related matters. Develop and deploy highly scalable distributed systems capable of handling petabytes of data. Architect and implement algorithms for data indexing and search capabilities. Build and maintain backend services for data storage, including work with key-value databases and synchronization. Deploy solutions in a Kubernetes Infrastructure-as-Code environment and perform routine system checks. Conduct and analyze experiments on data to provide insights into system performance. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in software development. Experience with large web crawlers a plus Strong expertise in large stateful distributed systems and data processing. Proficiency in Kubernetes, and Infrastructure-as-Code concepts. Willingness and enthusiasm for trying new approaches and technologies. Ability to handle multiple tasks and adapt to changing priorities. Strong communication skills, both written and verbal. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an

About the Team The Monetization team is a cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. In this foundational role, you’ll design infrastructure for conversion signals, attribution, reporting, and feedback loops across OpenAI’s ads products. This role is ideal for engineers who have built large-scale ads measurement, data, experimentation, marketplace, or distributed systems and want to apply that experience in a highly ambiguous 0→1 environment. You’ll work across event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy-safe aggregation, reporting, and high-quality labels for ads optimization. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You’ll work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Sc

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

About the Team The Monetization team is a new cross-functional group spanning engineering, product, research, and design. We are building the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to create user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen trust, expand economic opportunity, and support OpenAI’s long-term innovation. We believe monetization should deliver clear user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem for developers and businesses. The team operates in a greenfield environment, moving quickly through prototyping, experimentation, and iterative deployment. We partner closely across Product, Design, and Research to bring new capabilities into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build the integrity systems that keep OpenAI’s ads products safe, trustworthy, and resilient to abuse. In this foundational role, you will design infrastructure that detects and prevents harmful, deceptive, fraudulent, or policy-violating ads and advertiser behavior at scale. This role is well suited to an engineer who has built large-scale systems in ads integrity, trust and safety, anti-abuse, fraud, security, risk, or a related domain—and who wants to apply that experience in an ambiguous 0→1 environment. You will work across risk signals, detection and enforcement platforms, review tooling, adversarial resilience, advertiser controls, and integrity measurement. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You will collaborate with Ads Delivery, Ads ML, Product, Research, Safety, Policy, Privacy, Legal, Security, and operations teams to create a high-integrity ads ecosystem from first principles. This role is based in San Francisco. We offer relocation assistance t

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 The Applied team safely brings OpenAI's technology to the world. We released ChatGPT; Plugins; DALL·E; and the APIs for GPT-5, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. Our customers build fast-growing businesses around our APIs, which power product features that were never before possible. ChatGPT is a prime example of what is currently possible. We simultaneously ensure that our powerful tools are used responsibly. Safe deployment is more important to us than unfettered growth. The Fraud Engineering team works within our Applied Engineering organization identifying and responding to fraudsters on our platform. We are looking for a software engineer with anti fraud & abuse experience to help architect and build our next-generation anti-fraud systems. About the role The Scaled Abuse team protects OpenAI’s products and customers by detecting, preventing, and responding to fraudulent and abusive behavior at scale. We build and operate the backend and data systems that power real-time detection, investigation workflows, and enforcement — balancing strong protections with a great user experience as the platform grows. Our work sits at the intersection of engineering and abuse expertise: we partner closely with Trust & Safety, Security, and Product to understand emerging attack patterns, translate messy signals into clear system behavior, and continuously harden our defenses. The problems are dynamic and ambiguous by default, so we value engineers who can quickly dive into an unfamiliar codebase, develop strong intuition about how it works end-to-end, and propose pragmatic improvements that make the entire stack more resilient. In this role, you will: Design and build systems for fraud detection and remediation while balancing fraud loss, cost of implementation, and customer experience Work closely with finance, security, product, research, and trust & safety ope

About the Team The Post-Training Frontiers team is responsible for training the frontier agents OpenAI ships to the world (GPT-Next). We train the flagship agentic models behind Codex, ChatGPT, and the API through large-scale reinforcement learning. The team’s work spans four areas. First, execution and science: working with teams across OpenAI to decide what can go into the final model and how, using scientific experiments and evals that are representative of the final pipeline so issues can be recognized early. Second, RL scaling: executing the final large-scale reinforcement learning run, making sure GPUs are used efficiently and training stays healthy. Third, research: improving horizontal capabilities like instruction following, factuality, memory, and multi-agent behavior, where the team’s broad visibility helps identify cross-cutting improvements across teams and domains. Fourth, engineering: maintaining the infrastructure stack and internal tools to ensure that both the final run and all integrations go as smoothly as possible and that the systems are easy to work with. About the Role This role focuses on keeping our frontier RL training runs fast, reliable, and unblocked. You will work across engineering and infrastructure problems as they emerge, from scaling and orchestration issues to inference bottlenecks, numerical problems, and hardware failures, as well as supporting large horizontal integrations in the big run, like multi-agent capabilities or memory. This is a role for a strong generalist who quickly learns anything needed for the task, has high attention to detail, debugs deeply, and is motivated by fixing the highest-impact problem in front of the team. In this role, you will: Keep large-scale async RL training runs moving by jumping into the most urgent engineering and infrastructure problems. Debug issues across training systems, inference, orchestration, scaling, and distributed infrastructure. Improve the reliability and efficiency of RL trai

About the Team With Codex we’re building an AI software engineer. One that you can pair with, delegate to, or even ask to take on future tasks proactively. Our team is a fast-moving group within OpenAI, bringing together research, engineering, design, and product. We iteratively build the Codex agent harness and product to get the most out of the model, and we iteratively train the model to be great at complex software engineering tasks. The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. We operate across research, engineering, product, and infrastructure; owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. Codex Enterprise builds the ecosystem, governance, and enterprise capabilities that help Codex spread across developers, teams, and organizations worldwide. The User Activation team owns the product experiences that help developers discover Codex, understand its capabilities, connect it to their workflows, and turn initial usage into sustained adoption across teams. About the Role As Codex adoption grows, our challenge is no longer just building powerful AI capabilities. It is helping developers and teams quickly understand how Codex fits into their work, connect it to the tools and codebases they already use, and unlock workflows that make Codex feel like a true teammate. This role will help build the full-stack product surfaces that drive activation and adoption across Codex Enterprise. You will work across onboarding, workspace setup, integrations, discovery, collaboration, usage insights, and ecosystem capabilities that help Codex spread naturally through organizations. You will partner closely with product, design, research, infrastructure, GTM, and customers to identify where users get stuck, where teams fail to adopt Codex, and what product experiences can turn curiosity int

About the Team ChatGPT is evolving from answering questions to becoming a deeply personalized assistant that helps people discover, create, and make decisions across everyday life. We're building new multimodal product experiences that combine language, images, personalization, and interactive interfaces to help millions of users accomplish tasks in entirely new ways. This team sits at the intersection of AI research, product engineering, design, and consumer experiences. We move quickly, ship frequently, and work on products that define how people interact with AI every day. About the Role We're looking for exceptional full stack product engineers who love building polished consumer experiences from the ground up. You'll work across frontend, backend, AI-powered workflows, and rich interactive interfaces to create new product experiences that blend conversation, visual understanding, personalization, and commerce. You'll collaborate closely with designers, researchers, product managers, and model teams to rapidly prototype, launch, and iterate on experiences used by millions of people. This is an opportunity to help invent entirely new interaction paradigms—not just build traditional web applications. In This Role, You Will Design and build end-to-end product experiences across web services, APIs, and modern frontend applications. Partner closely with product, design, and research to rapidly prototype and launch new AI-native experiences. Build intuitive, performant interfaces that make advanced AI capabilities feel simple and delightful. Develop scalable backend systems that power personalized, real-time product experiences. Work with multimodal capabilities including text, images, and interactive UI components. Iterate quickly using user feedback, experimentation, and product metrics. Help define engineering standards, architecture, and technical direction for a fast-growing product area. You Might Thrive If You Have significant experience building consumer-facin

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

About the Team The Private Computing team works across product, engineering, security, and safety to build advanced privacy products and infrastructure at OpenAI. Our mission is to provide world-class security features to users so their private data remains private, even from OpenAI. We use technologies like confidential computing, trusted execution environments, and end-to-end encryption to ship product features across ChatGPT, the API, and our future consumer devices. About the Role We’re looking for software engineers to design, build, and scale novel privacy features and infrastructure across ChatGPT, API, and future consumer devices. In this role, you will: Ship fast while balancing difficult trade-offs in complex domains Build core abstractions for trusted execution environments and end-to-end-encryption Build product features for private inference and storage across ChatGPT, API, and future consumer devices Update build systems to increase trust and verifiability Integrate with safety and integrity infrastructure Operate systems at scale with high reliability, including an on-call rotation Collaborate with a diverse set of cross-functional teams across product, engineering, security, safety, policy, and legal You might thrive in this role if you: Care deeply about user privacy and security Have 5+ years of experience in professional software engineering Have experience building and scaling confidential computing or encryption technologies in production environments Have experience with Kubernetes and cloud orchestration systems Take pride in building and operating scalable, reliable, secure systems Can collaborate well and drive alignment in the face of difficult trade-offs Are comfortable with ambiguity and rapid change Workplace & Location This role is based in San Francisco, CA. We follow a hybrid model with 4 days a week in the office and offer relocation assistance to new employees. About OpenAI OpenAI is an AI research and deployment company dedicat

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. 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. About the Role We’re building the observability product for OpenAI—from scalable infrastructure to a rich, AI-powered UI. Our systems ingest over petabytes of logs and billions of time series metrics across our fleet. We're now layering intelligence on top—think agents that summarize SEVs, auto-generate dashboards, or help engineers debug through notebook-like UIs. We’re hiring software engineers across the stack—infra, backend, and product. You’ll join a small, gritty team building both foundational infra and novel internal tools to make OpenAI's production systems reliable, performant, and observable. What You’ll Do Own core observability infrastructure, including distributed logging, time series, and trace storage Build AI-native tools that help engineers detect, understand, and resolve issues autonomously. Contribute to UI experiences like dashboards, notebooking, or interactive debugging Collaborate closely with engineers, researchers, user ops, and other teams across the company to build the next generation observability product You Might Be a Fit If You: Have operated large-scale distributed systems in production. ( especially logging systems or some other time series databases) Thrive in ambiguous environments and roll up your sleeves to solve unscoped problems. Have full-stack chops or product sensibilities—you're excited to build real tools people use. Have strong fundamentals in systems, networking, and cloud infra (Kubernetes, AWS, etc). Bonus : built or contributed to observability systems (e.g. Prometheus, OpenTelemetry, etc). Why This Team We’re b

About the team The Applied team at OpenAI safely brings cutting-edge technology to the world. We have released groundbreaking products such as ChatGPT, Plugins, DALL·E, and APIs for GPT-4, GPT-3, embeddings, and fine-tuning. Our team also manages large-scale inference infrastructure. With much more on the horizon, our impact continues to grow. Our customers create fast-growing businesses using our APIs, enabling product features previously unimaginable. ChatGPT exemplifies the current scope of possibilities. We prioritize the responsible use of our powerful tools, valuing safe deployment over unchecked expansion. Within Applied Engineering, the Financial Engineering team ensures that our products are monetized effectively to accommodate customers' varying needs and scales. Collaborating closely with the GTM and Finance teams, we strive to tailor our billing stack to our evolving internal requirements. We seek an experienced engineer to architect and refine our billing systems, enhancing their functionality to meet the demands of our increasingly complex and expansive product offerings. In this role, you will: Architect and build the next generation of billing and monetization systems at OpenAI. Develop across the stack to create comprehensive billing integrations for our range of ChatGPT and API users. Design a versatile billing platform suitable for both subscription and usage-based offerings, ensuring scalability and enterprise readiness/flexibility. Construct and integrate tools that empower internal teams to seamlessly incorporate billing data into their workflows. Collaborate closely with a wide array of stakeholders, including the Product, Data, Finance, and Go-To-Market teams, as well as fellow engineers. You might thrive in this role if you: Possess a minimum of 5 years of professional software engineering experience, with added experience in payments, billing, or monetization seen as a bonus. Enjoy engaging with various partners, particularly those outside

About the Team The Cloud Agents team builds product infrastructure for long-running agents in the cloud: orchestration, sandboxing and isolation, secure environment connectivity, secrets and identity, observability, reliability, and cost controls. These agents securely connect to diverse developer and customer environments and use tools to accomplish goals. We partner closely with product, research, and infrastructure teams to turn agentic capabilities into dependable platforms for OpenAI products and developers building on OpenAI. About the Role We are looking for an experienced software engineer to help build and scale our cloud agent platform. You will design and operate systems for orchestrating agents at scale. You will work closely with product engineers on ChatGPT, API, and Codex to define the right abstractions and enable them to ship products quickly. Strong backend or infrastructure experience is important; experience with Python, Rust, distributed systems, cloud infrastructure, or product platforms is especially helpful. In this role, you will: Design and scale the orchestration, sandboxing and storage systems that run agentic workloads for Codex, ChatGPT, and the OpenAI API. Partner with product engineers to build a platform that enables them to ship quickly and turn feedback into robust abstractions. Improve reliability, security, performance, and cost efficiency for long-running agents. Deploy services that can operate across different environments and clouds. Your background might look something like: 9+ years of professional engineering experience, excluding internships, in relevant roles at technology and product-driven companies. Experience leading large-scale backend, platform, or infrastructure projects from ambiguous problem statements to production systems. Proficiency in one or more backend languages such as Python, Go, Rust, TypeScript, or similar, and the ability to move across service, platform, and product boundaries. Strong understanding