Infrastructure Team Manager in United States

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will work on the systems software strategy and execution that brings new AI silicon from first power-on to a fully integrated system running production-representative models at expected functionality and performance. You will define how software exercises and validates compute, memory, interconnect, and I/O subsystems, then build the diagnostics, automation, and observability needed to find issues quickly. This role sits at the center of silicon, firmware, platform, systems, and workload teams. You will turn hardware specifications and performance targets into an end-to-end bringup plan, drive cross-functional debug, and establish the stress and regression infrastructure that makes each new platform reliable across operating environments. In this role, you will: Contribute to the end-to-end software bringup and validation strategy for new silicon and first-party systems. Define software-driven test coverage across compute, memory, interconnect, I/O, and their system-level interactions. Build diagnostics, test automation, telemetry, and regression infrastructure that accelerate first-silicon learning and issue isolation. Lead bringup from initial silicon arrival through board and system integration, docking, runtime enablement, and model execution. Design stress tests that characterize reliability, performance, and stability across workloads and operating conditions. Translate architecture specifications and performance models into measurable acceptance crit

About the Team OpenAI's mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. The API Platform turns frontier research into reliable capabilities that developers use to build transformative products and services for people around the world. API Safety's goal is to ensure safe deployment of frontier models in the API. We design APIs and systems that help developers share usage context, understand safety events, and apply safeguards tailored to the risk profile of the applications they are building. This work is critical to our frontier model launches and partners closely with teams across API, Integrity, and Safety Research. About the Role We're looking for product-minded software engineers to join a team that is addressing emerging risks at the frontier of model development while building novel solutions for real-world AI deployment. The day-to-day work ranges from solving production challenges to designing new product experiences and safeguards. The right candidate is comfortable balancing tradeoffs across developer experience, latency, reliability, and risk. In this role, you will: Design and build dashboards and APIs for safety controls and customer-facing observability. Develop scalable systems that extend trusted safety capabilities to new use cases, customers, and deployment environments. Partner with Safety Research and Integrity to build safeguards that mitigate emerging risks. Be responsible for the availability, latency, and scalability of safeguards across high-volume API traffic. Own projects from technical design and implementation through launch and ongoing iteration, while raising the team’s engineering standards Your background might look something like: 7+ years of professional experience, excluding internships, in backend, infrastructure, platform, or product engineering roles. A track record of designing, building, and operating production backend services, developer-facing APIs, or distributed systems. Strong s

About the Team OpenAI’s People team is committed to hiring, engaging, and supporting world-class talent to help safely build and deploy universally beneficial Artificial General Intelligence (AGI). The People Operations team is responsible for the systems, data, and operational rigor that underpin every stage of the employee lifecycle. Our work sits at the intersection of employee experience, regulatory compliance, and business velocity — ensuring that as OpenAI scales rapidly and globally, our foundations remain accurate, auditable, and human-centered. This is a high-trust, high-impact function. We partner closely with Finance, Legal, IT, Security, and the broader People team to support growth in a dynamic environment with significant internal and external scrutiny. Operational excellence here is not about process for process’s sake — it is about building durable infrastructure that enables fairness, transparency, and responsible scale. About the Role As Director of People Operations, you will own the core operational infrastructure that enables OpenAI to scale responsibly. This role serves as the operational backbone of the People function, with accountability for data integrity, operational controls, and audit readiness across the systems that support a complex, global workforce, including the operational foundations of recruiting and hiring at scale. You will lead a team responsible for the end-to-end workforce lifecycle, from candidate and hiring operations through onboarding and offboarding, ensuring our people systems, processes, and data are accurate, resilient, and built to scale.In close partnership with Employment Legal and the People Compliance team, you will translate policy and regulatory requirements into scalable, well-controlled operational processes. This role operates with high visibility and close partnership with senior leaders across Finance, Legal, IT, and People, including ownership of SOX-relevant controls and workforce data relied upon by e

Datadog’s Implementation Services team helps customers implement and deploy Datadog quickly and successfully. Our team of architects leads the discovery, design, build, and launch of the Datadog platform to help customers accelerate time to value and get the most out of their investment. As a Senior Services Architect focused on Security and Cloud SIEM, you will help customers design, implement, and operationalize Datadog’s security capabilities across cloud, infrastructure, application, and log data sources. You will lead structured, outcome-driven professional services engagements delivered through a day-based professional services delivery model, partnering directly with customers through co-development working sessions, architecture workshops, implementation planning, and operational handoff. This role is ideal for someone who combines customer-facing consulting experience with strong cybersecurity knowledge, hands-on Cloud SIEM implementation skills, and an understanding of security control frameworks such as NIST 800-53, the NIST Cybersecurity Framework, CIS Controls, MITRE ATT&CK, SOC 2, PCI, HIPAA, ISO 27001, or similar standards. At Datadog, we place value in our office culture — the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design and guide execution of Datadog implementations, focusing on Security and Cloud SIEM deployment, including discovery, requirements gathering, technical architecture, deployment planning, and launch. Partner with customers to map security requirements, controls, and monitoring objectives to Datadog capabilities, including frameworks such as NIST 800-53, NIST Cybersecurity Framework, CIS Controls, MITRE ATT&CK, SOC 2, PCI, HIPAA, ISO 27001, or similar standards. Advise customers on security data strategy, including log source prioritization, parsing, normalizat

About the Team The Enterprise Identity team builds the identity foundation that enables organizations to adopt and use OpenAI products securely and reliably. The team owns the enterprise identity stack, including SSO, SCIM, tenant architecture, and identity capabilities across the enterprise admin experience and OpenAI's growing multi-product portfolio. About the Role We are looking for a hands-on senior technical leader to own the architecture and evolution of OpenAI's Enterprise Identity systems. You will set the long-term technical vision for the entire stack, establish shared identity primitives across products, and be accountable for systems that are foundational to our enterprise business. This role requires operating well beyond a single service or feature area. You will identify the most consequential architectural investments, align teams around durable solutions, and ensure our identity platform meets an exceptionally high bar for scale, availability, latency, and security. This role will be based in our San Francisco or Mountain View office. In this role, you will: Own the technical vision and architecture for the Enterprise Identity stack, including SSO, SCIM, tenant architecture, groups, permissions, and identity capabilities in enterprise administration surfaces. Lead the design and evolution of highly available, latency-sensitive identity systems serving a large and diverse global enterprise customer base. Establish common identity models and primitives that work consistently across OpenAI's products and enable the organization to scale. Set a high security bar by anticipating abuse cases, failure modes, and the long-term implications of new capabilities. Drive alignment across enterprise product, infrastructure, and security partners, resolving ambiguity and influencing roadmaps beyond the immediate team. Provide technical leadership to senior engineers and raise the quality of architecture and execution across the broader organization. You might thr

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 The GTM Intelligence Solutions team builds the data and decision systems that help customer-facing teams take the right action at the right time. We combine product telemetry, commercial data, customer context, and field activity to identify account health and opportunity, recommend actions and use cases, deliver intelligence through field-facing products and agent workflows, and measure what happens next. We’re looking for a Data Scientist to help build the next generation of GTM intelligence at OpenAI. You will own a flexible portfolio of high-impact decision data products and work closely with Technical Success and other GTM teams to ensure the work drives better decisions. About the Role As a Data Scientist on GTM Intelligence Solutions, you will define and build the intelligence systems that help customer-facing teams prioritize accounts, identify risks and opportunities, choose interventions, and understand what worked. You will set the roadmap and methodology, build canonical features, ship reliable production workflows, monitor quality and adoption, and improve the systems using field feedback and business outcomes. This role combines hands-on technical depth with strong product and business judgment. You should be as comfortable writing production Python and advanced SQL, defining durable data contracts, and operating decision products as you are evaluating a ranking approach or designing an experiment. You will personally ship reliable first versions and partner with Analytics Engineering and Data Engineering when work requires shared infrastructure or additional scale. In This Role, You Will Set the roadmap and methodology for GTM intelligence and decision products, using deep stakeholder discovery to probe beyond stated requests, uncover the underlying decisions, workflows, constraints, and measures of success, and translate them into measurable systems. Own the full lifecycle of intelligence products, including feature definition, methodo

About the Team The Legal team is building the next generation of AI-powered products and experiences for the legal industry. We are exploring how advanced AI systems can transform legal workflows, improve access to information, and enable legal professionals and organizations to work more effectively. As a founding member of the Legal engineering team, you will help define the technical foundation for this new product area from the earliest stages. You’ll operate at the intersection of AI, product, and real-world legal workflows—identifying opportunities, building prototypes, and turning emerging ideas into scalable products that can create meaningful impact. We operate with a startup-like mindset inside OpenAI: small teams, rapid iteration cycles, and a willingness to explore bold ideas, learn quickly, and adapt based on user feedback. Our goal is to build products that meaningfully improve how legal professionals work while leveraging OpenAI’s cutting-edge models and infrastructure. About the Role As a Founding Full-Stack Software Engineer on the Legal team, you will help imagine, build, and scale new AI-powered products for the legal industry. You’ll work across the stack to design intuitive user experiences, build robust backend systems, and create the foundations for products used by legal professionals and organizations around the world. You’ll have significant ownership from the earliest stages—working closely with product, design, research, and go-to-market partners to understand customer needs, shape product direction, and deliver high-impact solutions. This includes rapidly prototyping new concepts, building production-quality applications on top of OpenAI’s platforms, and developing new technical approaches when existing systems are not sufficient. We’re looking for engineers who thrive in ambiguity, have strong product instincts, and enjoy building from 0→1. You should be comfortable moving quickly, making thoughtful technical decisions, and taking owner

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 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 OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for an experienced systems software engineer to help define and build the host software stack for our custom next-generation AI systems. You will work close to the hardware on performance-critical software, including Linux kernel drivers, high-throughput I/O paths, and system-scale networking and RDMA. This role spans architecture, implementation, platform bring-up, debugging, and performance optimization. You will work across hardware and software boundaries to make new systems usable end to end, from low-level device interfaces through userspace tooling and production validation. In this role you will: Design, implement, and debug host-side systems software for AI infrastructure, including Linux kernel drivers and supporting userspace components. Build and optimize software paths for high-throughput, low-latency communication, including RDMA and related networking functionality. Develop software around PCIe, DMA, NICs, accelerators, memory movement, and device interaction. Bring up new hardware platforms and diagnose complex issues across kernel, firmware, networking, and hardware boundaries. Build tooling for integration, testing, diagnostics, observability, qualification, and performance characterization. Collaborate with hardware, networking, and platform teams to define interfaces and integrate new capabilities. Work with external vendors where needed to integrate technologies and drive issues to resolution. Contribute across the systems sof

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are looking for a hands-on lead to build and run OpenAI's Incidents & Escalations function within User Operations. This is a player-coach role with a meaningful hands-on operating component. You will set the operating model and also step into active incidents and urgent escalations when needed, coordinating with on-call teams, driving clear ownership, supporting communications, and ensuring issues move through resolution and post-incident closure. During active incidents, you will coordinate with the relevant on-call teams and cross-functional responders across Engineering, Infrastructure, Support Delivery, Product, and Go-To-Market. You will help keep teams aligned, maintain timelines, clarify ownership, escalate when needed, and ensure internal, executive, customer-facing, and external communications are accurate and timely, including status page updates when required. For escalations, you will build and run the processes for tracking, triaging, mitigating, and resolving critical customer and user issues. After incidents and escalations, you will own the follow-through: retrospectives, root cause identification, action item tracking, trend analysis, and process improvements that reduce repeat issues over time. You will also help define the long-term operating model for incidents and escalations across Support D

The ChatGPT Finances team builds experiences that help people connect their financial accounts, understand their financial picture, and ask useful questions about their finances through ChatGPT. Our work spans account connectivity, data ingestion, dashboards, personalized insights, and conversational experiences. We collaborate across product, design, research, infrastructure, security, and data integrations to make complex financial information understandable and actionable. This is an early and ambitious product area with a substantial roadmap. We are looking for engineers who want to shape both the first user experiences and the durable systems required to earn and keep users’ trust. About the role We’re looking for full-stack product engineers to build and scale ChatGPT Finances. You will own features across the stack—from polished frontend experiences to the APIs, services, and data models that power them. This role is well suited to engineers who combine strong product judgment with broad technical depth. You should care about how quickly users can understand their financial lives, how reliably data moves through the system, and how AI can answer financial questions in a grounded, transparent, and useful way. You will work closely with product, design, research, infrastructure, security, and data integration teams to take ideas from early prototypes to reliable production experiences. In this role, you will Own full-stack product features from user experience and frontend implementation through backend services, data models, deployment, and observability. Build polished, accessible, and performant interfaces for account connection, dashboards, insights, and conversational workflows. Design APIs and backend systems that safely ingest, normalize, and serve financial data. Build resilient integrations that handle synchronization, data freshness, partial failures, permissions, and user consent. Bring new AI capabilities into production while prioritizing grounding

About the team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you'll: Create ambitious RL environments to push our models to their limits, and measure frontier

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Connectors, you will teach models how to interface with the top professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use. You will train models to be supercharged by the world’s most important productivity and enterprise software, turning connected tools into a powerful action surface for our agents. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people.