Ai And Cloud Service Provider Account Executive in United States

About the Team OpenAI's Human Data Team creates custom data solutions driving groundbreaking research. Our work enhances and evaluates our flagship models and products like ChatGPT, GPT-5, and Sora, and contributes to safety initiatives through collaboration with our Preparedness and Safety Systems teams. About the Role As a Research Program Manager (RPM) in the Human Data team you will partner with research and engineering to design and implement pragmatic solutions for collecting high-quality data. You will be a key interface between our research roadmap, external vendors, AI trainers, and the Human Data engineering team. This role is based in our San Francisco HQ. In this role, you will: Collaborate with Research: Partner with researchers to scope data collection needs, define success metrics, and establish quality measurement frameworks. Design & Execute Data Collection Campaigns: Translate research needs into actionable plans and accelerate execution by leveraging existing tooling and iterating to reach the desired outcome. In many cases, you will need to implement scrappy new solutions while partnering with engineering to design robust/scalable solutions. Unblock Yourself: You must be deeply uncomfortable with the idea of sitting around waiting for external dependencies, and have the technical acumen and drive to figure out how to achieve at least partial success in the interim. Optimize Systems & Processes: Build and optimize dashboards to track campaign performance, leveraging SQL and Python for data analysis and actionable insights. Drive Technical Roadmaps: Collaborate with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management. Scale Your Impact : Advise and empower program managers and vendors to drive day-to-day execution so that you can focus on addressing high priority opportunities. You might thrive in this role if you: Are proficient in SQL and Python for data analysis, including q

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role We are seeking a Software Engineer, Security Observability to join our Security team. In this role, you will be responsible for building secure, scalable systems that enhance our security observability infrastructure. Leveraging your strong engineering skills, you will collaborate with cross-functional teams to develop, deploy, and maintain robust software solutions that support our security and detection capabilities. This role is open to remote employees, or relocation assistance is available to one of our OpenAI offices in San Francisco, Seattle, or New York City. Due to requirements associated with work this role may support, applicants for this position must be U.S. citizens. In this role, you will: Design and develop scalable software systems that facilitate security observability across our infrastructure. Build and maintain data pipelines that centralize and store security-relevant data from diverse sources. Proactively improve the resilience and reliability of data systems to ensure high platform availability Collaborate closely with Detection & Response (D&R) and other security teams to reduce the company’s security risk. Contribute to data engineering in support of forensic investigations and compliance efforts. You might thrive in this role if you have: Strong software engineering experience, with proficiency in programming languages such as Python, Golang, or similar. A background in infrastructure as code, with exp

About the Team OpenAI’s Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally. We tackle some of the company’s most important challenges across understanding and preventing misuse and misalignment, intercepting fraud and abuse, and protecting vulnerable users. We are hiring Data Scientists to help build the analytical foundations that allow OpenAI to deploy increasingly capable AI responsibly. We are hiring Data Scientists across several teams that contribute to safety in different ways, including: Safety Systems Integrity Product Policy This is a high-impact role operating at the intersection of product, safety, policy, and research. About the Role As a Data Scientist, Safety, you will help solve complex and ambiguous problems where rigorous analysis directly informs critical decisions. Depending on your background and team alignment, you may work on areas such as: Measure harmful or abusive behavior across OpenAI’s products Detect fraud, manipulation, coordinated misuse Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows Design experiments and causal analyses to understand product, policy, and mitigation impacts Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks Diagnose gaps in safety and integrity systems using behavioral and product data, and help quantify and navigate false positive / false negative tradeoffs Translate ambiguous safety risks into measurable problems and evidence-based recommendations Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes Build zero-to-one analytical systems in rapidly evolving domains Ideal Candidate We’re looking for strong Data Scientists who thrive in ambiguous, high-leverage environments. You may be a fit if you have: Strong statistical reasoning and analytical judgment Experience with experimentation, causal inference, or obse

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the Team Training Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters. Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale. About the Role We are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks. You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training. In this role, you will Design and build a unified dataset read platform for multiple current and future training frameworks. Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable. Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts. Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role As a Security Engineer, Application Security you will be responsible for identifying and mitigating security vulnerabilities within software applications through building security tools, code reviews, penetration testing, and security assessments. We’re looking for people who will work closely with development teams to ensure secure coding practices are integrated throughout the software development lifecycle, preventing security risks before they emerge. You will also provide security guidance to developers and other stakeholders, fostering a culture of security awareness within the organization. The role is preferred to be based in San Francisco, Seattle or New York City but may consider remote work. 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: Perform Security Assessments : Conduct regular security assessments, code reviews, and penetration testing to identify vulnerabilities in applications and software. Develop and Implement Security Tools : Design, develop, and implement security tools, frameworks, and methodologies to protect applications against security threats. Collaborate with Development Teams : Work closely with development teams to ensure security best practices are integrated throughout the software development lifecycle (SDLC), including secure coding guidelines. Threat Modeling and Risk Assessment : Conduct threat modeling and risk

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Industrial Compute team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role The Community Engagement Lead will serve as the primary liaison between OpenAI and the communities where it plans to develop data centers, including Effingham County and the greater Savannah Metropolitan Area. This role ensures that OpenAI builds strong, trust-based relationships with local stakeholders, communicates proactively about our projects, and integrates community priorities into our development approach. The role spans engagement, communications, and reputation management, and will partner closely with the Economic Development and Environmental leads. Key Responsibilities Build and maintain relationships with local leaders, community organizations, NGOs, and residents. Develop and execute community engagement strategies for new and existing sites. Represent OpenAI in public forums, hearings, and community events. Partner with the Economic Development Lead on incentive compliance and community benefits. Partner with the Environmental Lead on communicating environmental stewardship and sustainability efforts. Develop proactive communications to address concerns, highlight benefits, and reduce risk of opposition. Monitor community sentiment and advise executives on risks and opportunities. Create a community engagement playbook that can scale across geographies. Qualifications 8+ years in community affairs, public engagement, or corporate communications. Proven track record engaging diverse community stakeholders for large infrastructure or technology projects. Strong publ

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role As a foundational FDE manager, you’ll lead FDE through high-stakes, ambiguous customer deployments and own technical and business value outcomes end to end. You’ll grow a team that can operate under pressure and help OpenAI learn from the field. You’ll partner closely with Product, Research, Sales, and GTM to ensure fieldwork informs roadmap priorities, drives new exploration, and supports safe deployment at scale. Your decisions will influence how OpenAI is trusted by the customers closest to our deployment work. Your success will be measured by how consistently your team ships, how clearly you deliver signal to Research and Product, and how durable your team and delivery model prove to be. This role is based in New York City We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. This role also will require travel up to 25%. In this role you will Lead and grow a team of FDE delivering production systems with frontier models Own end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality Codify what works into tools, playbooks, and roadmap inputs that create leverage for both OpenAI and our wider developer community Notice early indicators and raise them with urgency, whether in product behavior, customer environments, or delivery practices Use judgement to distinguish what requires action and what does not Set a high bar for FDE performance and support each person’s growth through direct, actionable feedback Define how we staff and support field teams that can scale without added complexity You might thrive in this role if you Bring 8+ years of engineering or technical delivery experience, including 2+ years managing high-performing FDE or custo

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the Role We are looking for customer-focused software engineers to build effective custom software that leverages OpenAI’s APIs to solve real customer problems. As an FDSWE, you will work with our customers and OpenAI Forward Deployed Engineers to design and implement scalable solutions that solve their most difficult problems. You will design abstractions to solve customer problems, and then use them to scale our speed and quality of delivery across all Forward Deployed engagements. You will collaborate closely with Sales, Solutions Engineering, Solutions Architects, and Customer Success Managers who work on the same account. You will also work with our Research and Applied Product and Engineering teams to provide insightful customer feedback. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role, you will: Embed deeply with strategic customers to understand their business challenges and technical requirements in detail. Design, architect, and develop full-stack solutions using an experiment-driven, iterative approach. Prepare detailed scopes of work and project plans for both proof-of-concept prototypes and full production deployments. Work hands-on with customers' technical teams as a technical expert and trusted advisor, coding side-by-side to drive projects to completion on their infrastructure. Collaborate with Product, Research and Applied teams to ensure seamless customer experiences, project success and actionable product feedback Contribute to internal knowledge bases, codifying best practices and sharing insights gained from customer engagements to scale the Forward Deployed Engineering function. You’ll thrive in th

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, Computer Use, you will teach models to operate computers. You will help train models that can navigate browsers and desktops, use tools and applications, reason through complex workflows, collaborate with users and other agents, and complete long-horizon tasks with reliability and judgment. This work sits at the intersection of frontier model training, product behavior, evaluation, and systems engineering, and will directly shape the computer-use capabilities shipped in OpenAI’s next generation of agents. Currently, our models are the best in the world at this behavior! 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 might Design and run experiments th

About the Team Our team brings OpenAI’s most capable technology to the world through our developer platform: the OpenAI API. As the leading AI development platform, our API is used by millions of developers and the majority of enterprises around the world, and powers the majority of AI applications that you may use on a daily basis. The platform supports everything from simple model calls to stateful, multimodal, tool-using applications through the Responses API, Agents SDK, Realtime API, and more. Our SDKs turn that fast-moving platform into reliable, idiomatic developer experiences across languages. About the Role We are looking for a software engineer to help build the official SDKs that power the OpenAI API. Currently offered in Python, Node.js, Golang, Java, and Ruby – our SDKs are some of the most popular in the world. You will help shape the developer experience for all new API features, as well as all future versions of our APIs. We’re looking for engineers who are deeply immersed in AI-native development: people who actively build with Codex and other coding agents, have developed agentic applications or developer tools, and bring strong, experience-backed opinions about OpenAI’s APIs. You’ll pair that firsthand product intuition with meticulous SDK design to improve how developers build with our platform. Prior experience building SDKs is lovely, but not absolutely necessary. In this role, you will: Define and implement the SDK experience for all new API features, as well as all future versions of our API. Build and experiment with agentic applications, developer tools, and coding-agent workflows using Codex and OpenAI’s APIs, translating firsthand experience into better SDK abstractions, API ergonomics, and developer experiences. Build and maintain our systems to make SDK maintenance and generation streamlined and automated. Contribute to our SDK strategy and roadmap, including which languages to support and what features to support. Collaborate closely w

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role Our technologies support some of the most important and impactful work in the world, including our strategic and high-impact customers in the public sector. As a Forward Deployed Security Engineer (FDSecE) you will be responsible for securing these novel applications of OpenAI’s technology. We’re looking for motivated, tenacious, and curious people who will work closely with engineering teams to ensure our infrastructure deployments are highly secure against our adversaries. As an FDSecE, you will embed directly throughout the lifecycle, working on-site and being hands-on to ensure the overall security of these deployments from design to production and through ongoing operations. This role is preferred to be based in Washington DC but may consider remote work. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Travel to and working from customer sites is required for this role. In this role, you will: Deeply embed with our most strategic public sector customers to implement and maintain robust security controls. Be a design and technical thought partner by leveraging security expertise on protective controls including access controls, authentication, encryption, network, and system security. Collaborate closely with teammates, cross-functional teams, customers, and service providers to achieve security and compliance goals. Ensure continuity of critical security and monitoring c

About the Team Frontier Systems Foundations, part of Compute Foundations at OpenAI, builds the systems software foundation that turns new compute infrastructure into reliable, usable capacity for frontier model training. Our mission is to make some of the world's largest GPU clusters work reliably for frontier training. We bring new platforms and clusters online, safely maintain installed fleets, and partner with hardware, infrastructure, and research teams to resolve the system-level issues that keep jobs from running. That means building and maintaining the software closest to the machine: Linux and Ubuntu operating-system images, kernels and modules, drivers, packages and repositories, disks and boot configuration, firmware integration, provisioning, and system-level validation. We make these components reproducible, compatible, and safe to operate across heterogeneous fleets. About the Role We are looking for systems software engineers with deep Linux and host-systems experience to build, qualify, and maintain the operating-system foundation for OpenAI's frontier compute fleet. Relevant backgrounds include kernel and module development, Linux distribution or image engineering, package management, firmware and driver integration, disks and boot, and bare-metal provisioning. You'll work closely with hardware engineers, vendors, and infrastructure teams to bring up new platforms, integrate system components, and debug failures across firmware, disks, boot, operating systems, kernels, drivers, and workload interactions. Your work will directly influence how quickly new capacity becomes usable and how reliably large GPU fleets operate. You should be comfortable writing and maintaining production-quality systems software and automation, but we do not expect expertise across every layer. This is an opportunity to go deep on challenging systems problems while building the image, package, qualification, and recovery paths that power the next generation of frontier models

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, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. This work will require owning improvements across our post-training stack, including RL, data pipelines, graders, reward signals, evals, and behavioral analysis. 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 will: Design and run experiments that improve agentic model behavior for complex so

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Infrastructure team is central to this mission, setting the core strategy and implementing the vision. From site selection to deployment to operations, this team sits at the intersection of commercial, technical, and operational domains, interacting with experts and executives inside and outside of OpenAI. We design and operate mission-critical facilities that support cutting-edge AI workloads at scale. About the Role We are seeking a Facilities Operations Lead to support the commissioning, deployment, and long-term operation of our next-generation AI data centers. This role bridges the interface between data center construction and hardware landing, ensuring seamless integration of mission-critical infrastructure with hardware deployment timelines. You will define and execute commissioning plans, support infrastructure bring-up, and take ownership of operations and maintenance for cutting-edge, large-scale, AI data centers. You will collaborate closely with design, construction, and hardware teams to define repeatable processes for new data center builds and lead hands-on operations to uphold the performance and reliability of our deployed infrastructure. Key Responsibilities Define and execute sequences of operations, commissioning steps, and bring-up processes for mission-critical data center facilities. Interface with the design and hardware teams to define deployment procedures tailored to each data center and hardware configuration. Oversee installation, commissioning, and operational readiness of large-scale data center campuses. Manage monitoring, maintenance, and quality control of the data center infrastructure, including high-performance liquid cooling systems. Develop on-site operations staffing strategy. Develop and enforce procedures for planed and unplanned downtime and SLAs for critical