Ai Systems Engineer in United States

About the Team The ChatGPT Search Product Infrastructure team builds the foundational systems that power search experiences across ChatGPT. We develop the product infrastructure that connects models with search systems and other sources of real-time information, enabling ChatGPT to deliver timely, relevant, and trustworthy answers to users around the world. Our work sits at the intersection of product engineering, AI, and large-scale infrastructure. We build shared platforms and abstractions that enable product teams to independently develop, evaluate, and launch new search-powered experiences. These platforms provide the guardrails, testing capabilities, observability, and rollout controls needed to prevent reliability, scalability, quality, and latency regressions while supporting rapid product iteration. The team partners closely with: Post-Training on model launches, experimentation, and prompt optimization Search product verticals on new user experiences Inference on GPU efficiencies Indexing and Retrieval on the systems that identify and deliver relevant information Capacity/Fleet team to ensure optimal regionalized provisioning of GPUs and CPUs About the Role We are looking for an Engineering Manager to lead the team responsible for ChatGPT’s Search Product Infrastructure. You will set the technical and organizational direction for the systems that bring search capabilities into ChatGPT. You will guide architectural decisions across search orchestration, model and prompt integration, serving infrastructure, experimentation, observability, evaluation, and product integrations. You will balance immediate launch and product needs with the long-term reliability, scalability, latency, and maintainability of the platform. A central responsibility of this role is creating leverage for Search product verticals. You will lead the development of extensible platforms that allow those teams to independently build, test, and launch features without requiring ongoing invol

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 We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. 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 OpenAI is looking for an experienced Performance Engineer to help us scale the performance, reliability, and efficiency of our systems. In this role, you'll apply deep technical expertise to optimize infrastructure and application-level performance across mission-critical products like ChatGPT and our developer API. You’ll work cross-functionally with teams building core services, training models, and developing real-time user experiences to push our latency, throughput, and cost-efficiency to the next level. We are looking for engineers who thrive in ambiguous environments, value deep systems understanding, and are motivated by delivering measurable impact. This is a highly technical, individual contributor role focused on root-cause analysis, profiling, instrumentation, and architecture-level performance improvements across our stack. In this role, you will: Analyze and optimize performance across application, middleware, runtime, and infrastructure layers—networking, storage, Python runtime, GPU utilization, and beyond. Develop tooling and metrics that provide deep observability into system performance. Collaborate closely with infra, platform, training, and product teams to identify key performance goals and drive systemic improvements. Influence architecture and design decisions to prioritize latency, throughput, and efficiency at scale. Lead investigations into high-impact performance regressions or scalability issues in production. Drive performance testing strategies and help define SLAs/SLOs around latency and throughput for critical systems. You might thrive in this role if you: Have 7+ years of experience in software engineering with a strong tr

About the Team At OpenAI, we’re building safe and beneficial artificial general intelligence. We deploy our models through ChatGPT, our APIs, and other cutting-edge products. Behind the scenes, making these systems fast, reliable, and cost-efficient requires world-class infrastructure. The Caching Infrastructure team is responsible for building a caching layer that powers many critical use cases at OpenAI. We aim to provide a high-availability, multi-tenant cache platform that scales automatically with workload, minimizes tail latency, and supports a diverse range of use cases. We’re looking for an experienced engineer to help design and scale this critical infrastructure. The ideal candidate has deep experience in distributed caching systems (e.g., Redis, Memcached), networking fundamentals, and Kubernetes-based service orchestration. In This Role, You Will: Design, build, and operate OpenAI’s multi-tenant caching platform used across inference, identity, quota, and product experiences. Define the long-term vision and roadmap for caching as a core infra capability, balancing performance, durability, and cost. Collaborate with other infra teams (e.g., networking, observability, databases) and product teams to ensure our caching platform meets their needs. You Might Thrive In This Role If You: Have 5+ years of experience building and scaling distributed systems, with a strong focus on caching, load balancing, or storage systems. Have deep expertise with Redis, Memcached, or similar solutions, including clustering, durability configurations, client-side connection patterns, and performance tuning. Have production experience with Kubernetes, service meshes (e.g., Envoy), and autoscaling systems. Think rigorously about latency, reliability, throughput, and cost in designing platform capabilities. Thrive in a fast-paced environment and enjoy balancing pragmatic engineering with long-term technical excellence. About OpenAI OpenAI is an AI research and deployment company d

We take play seriously. We’re looking for curious adventurers ready to find their party, fueled by imagination and drive to build what’s never been built before. At Hasbro and Wizards of the Coast, you’ll collaborate with passionate teams to reimagine our iconic brands and create experiences that spark joy, connection, and community through the magic of play. This is your chance to shape legendary play that lasts a lifetime. We're building something new inside our AI Studio, and we're looking for a Customer Success Engineer to help shape it with us. This role sits at the center of a new and constantly evolving business area. The problems are still taking shape, and the systems are actively being built. What excites us is the opportunity to push the boundaries of what stories and characters can be and to use technology to bring iconic IP to life in ways never before imagined. We work where storytelling, imagination, and technology converge. Our focus is on defining and building the core systems that transform characters and worlds from something audiences watch into something they can interact with and engage over time. This role is the bridge between our platform and the partners building on it. Working within the engineering team, this Customer Success Engineer will help customers take character experiences from first prototype through production, then turn what they learn in the field into a platform that needs less hand-holding each time. Success here means partners shipping faster, and the internal team never being surprised by what customers are experiencing. What You'll Do Knowing is half the battle. Implementing is the other. One week you're pairing with a partner team to get their first character experience working; the next you're turning that engagement's rough edges into a better SDK, a clearer code example, or documentation that answers the questio

About the Team The Applied organization brings OpenAI’s most advanced technology to the world through products like ChatGPT and the APIs that power a growing ecosystem of developer and enterprise applications. Data Engineering builds and operates the trustworthy, secure, and reliable data systems that power decisions across OpenAI. About the Role We’re looking for a Data Engineering Manager to lead the Growth & Revenue data engineering team. This leader will own the data strategy and execution for the data subject areas spanning growth accounting across all product surfaces, product partnerships, checkout, billing, payments, revenue, and monetization, helping OpenAI understand how people adopt, engage with, and pay for our products. You will partner closely with several Data Science, Business, and Engineering partners to connect product behavior to trustworthy subscriber, payment, and revenue measurement. In this role, you will: Build, manage, and grow a high-performing, inclusive team across the Growth & Revenue data subject areas. Define the data strategy for all the data subject areas you own. Deliver durable, well-modeled data products that connect product behavior, subscription state, checkout events, payment outcomes, and revenue. Establish trusted metric definitions and data quality standards so product, growth, finance, and executive leaders can make fast, consistent decisions. Partner with Data Science and Product teams to support experimentation, causal measurement, funnel analysis, and scalable self-serve analytics. Partner with Finance and Financial Engineering to ensure analytical revenue views reconcile to financial truth and production billing systems. Raise operational excellence for critical pipelines, including reliability, observability, privacy, governance, and incident response. Set a clear roadmap, make principled tradeoffs, and communicate progress and risk across technical and business stakeholders. You might thrive in this role if yo

About the Team The ChatGPT organization at OpenAI supports our mission by bringing advanced AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language. Recent advances in our multimodal image models have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering, unlocking entirely new creative and professional workflows. We work at the intersection of research, infrastructure, and product to build the systems that power image generation at global scale. Our team partners closely with researchers, product engineers, designers, and platform teams to bring state-of-the-art image capabilities to millions of users while continuously pushing the boundaries of what AI-powered creation can do. About the Role We are looking for an experienced Backend Engineer to join the Image Generation team and help build the systems that power image creation and editing across ChatGPT. You'll work on the core backend infrastructure that enables users to generate, edit, and iterate on visual content using cutting-edge multimodal AI models. This includes building highly scalable services, orchestration systems, APIs, storage platforms, and distributed infrastructure that support billions of image generations and editing workflows. You'll partner closely with product, research, and mobile teams to transform breakthrough AI capabilities into reliable, performant experiences used by millions around the world. In this role, you will: Design, build, and operate backend systems that power image generation and image editing experiences in ChatGPT. Develop scalable APIs, services, and infrastructure that support multimodal AI workflows. Optimize reliability, latency, throughput, and cost across large-scale distributed systems. Partner with researchers to productionize new im

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in the US or can be based out of any of our US offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's

About the Team OpenAI for Financial Services is part of OpenAI's Verticals organization, which focuses on accelerating the economy and knowledge work. We build AI products for financial institutions and the professionals who power them, from investment bankers and research analysts to investors and other financial services teams. We combine OpenAI's models, financial data, and enterprise knowledge to help professionals research companies, analyze markets, and produce high-quality work in the tools they use every day. We're a small, entrepreneurial team working closely with customers and partners across research, product, design, engineering, and go-to-market to bring new capabilities from idea to production. About the Role We're looking for backend engineers to build the systems that make advanced AI useful, reliable, and trustworthy in financial services. You'll build the data systems, agentic workflows, and enterprise integrations behind our products. You'll also help bring them into production at some of the world's largest financial institutions. This is a product-minded engineering role with significant ownership and zero-to-one building. You'll shape new products from the ground up, work directly with customers to understand their workflows, and collaborate across OpenAI to turn new model capabilities into products that professionals can trust with high-stakes work. In this role, you will: Design and build backend systems that power AI-native financial workflows across ChatGPT Work and Codex. Build infrastructure to ingest, index, retrieve, and serve financial data, company filings, market information, and firm-specific knowledge at scale. Develop integrations with financial data providers, enterprise knowledge systems, and customer environments, including the authentication, authorization, and entitlements required to use them securely. Build the systems that let models and agents use the right tools and data, preserve source provenance, and produce accurate,

About the Team OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible. This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness. About the Role We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments. This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality. In this role, you will Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance Bu

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

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 Monetization team is a new 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, advertisers, and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, Research, and external customers to bring new monetization products into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build Ads Manager, the UI platform advertisers use to create, manage, measure, and optimize ad campaigns across OpenAI’s ads ecosystem. This is a foundational role responsible for designing and implementing advertiser-facing products, APIs, tools, and services that connect external customers to OpenAI’s next-generation monetization products. You’ll work across the full technical stack to build intuitive self-serve workflows for small and mid-sized advertisers, as well as scalable APIs and integrations for large enterprise advertisers, agencies, and ad-tech partners who manage campaigns through their own buying platforms or intermediary systems. This includes building advertiser-facing APIs and tooling for campaign management, conversion APIs, pixels, measurement, and insights. You will collaborate deeply with Product, Design, Research, and Go-To

About the Team The Monetization team is a new 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 help build the machine learning infrastructure that powers OpenAI’s monetization and ads systems. In this foundational role, you’ll design and develop the platform layer that enables teams to build, train, deploy, serve, monitor, and continuously improve machine learning models used across advertising and monetization products. You’ll work across the full ML lifecycle, from large-scale data pipelines and feature infrastructure to training systems, model serving, experimentation platforms, and monitoring frameworks. The systems you build will support high-throughput, low-latency advertising workloads while maintaining strict standards for reliability, privacy, security, and performance. This role sits at the intersection of machine learning systems, distributed infrastructure, and monetization, offering the opportunity to shape the core platforms that help translate model innovation into m

About the Team The Monetization team is a new 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, advertisers, 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 new ad experiences into real-world systems across OpenAI surfaces at global scale, including thoughtfully integrating them into the core ChatGPT experience. About the Role We’re looking for an experienced Software Engineer to help build the creative rendering and presentation layer of OpenAI’s ads ecosystem. This is a foundational role responsible for defining how ads are structured, rendered, and delivered across different surfaces, platforms, and media types. You’ll work across the full technical stack to build infrastructure and tooling for new ad formats, including text, image, video, native, conversational, and interactive experiences. You will help ensure these formats render reliably, perform efficiently, and feel natural within the core ChatGPT experience. You’ll collaborate deeply with Product, Design, and Research to create ads experiences that are useful, high-quality, privacy-preserving, and aligned with OpenAI’s standards for safety and user trust. In this role, you will: Design, build, and