Product Support Operations Director in United States

About the team OpenAI’s Enterprise Go-To-Market organization helps the world’s largest companies adopt and scale our AI platform across their business—from ChatGPT Enterprise to our developer platform and APIs. We partner with organizations across Financial Services, Life Sciences, and Retail to build new AI-powered customer experiences, transform operations, and reimagine how work gets done in highly regulated and technically complex environments. As adoption accelerates through pilots, experimentation, and developer-led use cases, the GTM team turns that momentum into durable, enterprise-wide deployments. Sales Development sits at the front of this motion—where technical curiosity becomes executive engagement and OpenAI’s enterprise relationships begin. About the role We are hiring a Sales Development Manager, AMER to lead a team of SDRs supporting our Large Enterprise business across North America. Reporting into Sales Development leadership, this role will be responsible for coaching and developing a high-performing team focused on generating qualified pipeline and creating strategic enterprise opportunities. This is a foundational front-line leadership role within OpenAI’s enterprise GTM organization. You will help define how we engage prospective customers, convert product and developer interest into enterprise conversations, and scale repeatable outbound and inbound motions across some of the world’s largest organizations. You will partner closely with Sales, Marketing, Solutions Engineering, Partnerships, and Strategy & Operations to drive pipeline generation and help shape the future of OpenAI’s enterprise growth engine. In this role, you will: Lead, coach, and develop a team of SDRs supporting Large Enterprise, Verticals, and Strategic Accounts across AMER Drive high-quality pipeline generation through outbound prospecting, inbound qualification, account-based motions, and product-led signals Establish strong operational rigor around activity metrics,

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. Learn more about OpenAI’s approach to safety About the Role As an Analytics Engineer in Safety Systems, you will play a pivotal role in building a data-centric culture, enhancing decision-making processes, and driving strategic initiatives through analytics. You will partner closely with Engineering, Research, and Data Science to develop and maintain canonical data sources and source-of-truth dashboards that enable both people and AI agents across the organization to derive trustworthy, actionable insights. You will own the consumption layer for safety metrics: defining intuitive, reliable ways for stakeholders across Safety Systems, partner teams, and leadership to understand the safety of our products, answer safety-related questions independently, and inform product decisions and company strategy. Most importantly, you will be a core member of the Safety Systems team, collaborating with researchers and engineers to advance our goals of safe, robust, and reliable AI. This role is based in San Francisco, CA. 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: Design and maintain canonical datasets that serve as sources of truth for safety metrics. Develop and refine data products such as dashboards, reports, agent-enabled workflows, and machine-readable interfaces that empower stakeholders to extract and analyze data independently. Work closely with stakeholders in Engineering, Research, and Data Science to understand their decision-making n

About the Role The Engineering Acceleration team builds and operates the foundational systems that engineers use to build, test, and ship ChatGPT, the API, and OpenAI's infrastructure. We are looking for an engineer to help evolve OpenAI's build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, and software quality. You will work on the systems that determine how quickly and confidently engineers can move: Bazel-based builds, Buildkite pipelines, test selection, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to make OpenAI one of the most productive engineering organizations in the world while preserving a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping useful systems instead of fighting infrastructure. In This Role, You Will Own and evolve Bazel-based build and test workflows across a large, polyglot monorepo. Design and maintain Starlark rules, macros, toolchains, and integrations that make builds reproducible, hermetic, and easy for product teams to adopt. Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, test sharding, retry behavior, and flake isolation. Build systems that reduce unnecessary CI work through affected-target detection, dependency graph analysis, test selection, caching, batching, and smarter scheduling. Improve local development workflows so engineers can reproduce CI behavior, debug build failures, and iterate quickly without learning every detail of the build stack. Operate and optimize build infrastructure across Docker/OCI images, Kubernetes-based runners, cloud resources, and remote cache/exec

About the Team The Human Data team at OpenAI is responsible for identifying and mitigating risks in advanced AI systems by designing evaluations, surfacing vulnerabilities, and collaborating closely with researchers to strengthen model reliability and public trust. About the Role As a Research Program Manager, you will lead initiatives that test the safety and robustness of OpenAI’s models through creative experimentation and structured evaluation. You’ll coordinate efforts across research and engineering teams to transform ambiguous risks into concrete research programs and influence future model development and deployment. We’re looking for people who are technically savvy, comfortable with ambiguity, and excited about shaping the future of safe AI. This role is based in San Francisco, CA. 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: Lead programs that explore unexpected model behaviors and identify failure modes. Translate vague or emergent risk signals into clear priorities and actionable research plans. Design and run creative evaluations, experiments, and red-teaming campaigns. Collaborate with research, product, and deployment teams to integrate findings into model training and deployment cycles. Develop repeatable systems for tracking model performance and understanding emerging behavior patterns. You might thrive in this role if you: Have strong experience in technical program management, with excellent organizational and communication skills. Are familiar with large language models, prompt engineering, or model evaluation techniques. Are comfortable managing fast-paced, high-uncertainty projects and shaping them from the ground up. Are creative and resourceful in devising new methods for testing model behavior and performance. Can effectively coordinate across technical and non-technical stakeholders to drive alignment and execution. About OpenAI OpenAI is an AI resear

About the Team The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework . Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models. The mission of the Preparedness team is to: Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards misuse risks whose impact could be catastrophic to our society Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems Preparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society. About the Role We’re hiring a Data Scientist to help build, evaluate, and continuously improve mitigations that prevent extreme harms from AI systems. This role is for an experienced, highly autonomous individual contributor who can take ambiguous problem statements, structure rigorous analyses, and translate findings into actionable product and policy changes. This position goes beyond “running evals.” You’ll help create mitigation intelligence and monitoring systems that enable OpenAI to detect issues early, measure effectiveness over time, and reduce both over-blocking (unnecessary friction) and under-blocking (missed harm). What You’ll Do Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains (e.g., biosecurity, cybersecurity, and emerging risk areas). Diagnose false positives and fa

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: Experience building systems in adversarial, fast-evolving environments Are comfortable with ambiguity and novelty Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. Significant experience

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 AWS-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 AWS-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 hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration. You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time. In this role, you will Partner with strategic customers and in

About the Team At OpenAI, we are dedicated to building safe artificial general intelligence (AGI) to benefit all of humanity. Our mission attracts the world’s top talent in science, engineering, and business to address one of the most ambitious challenges of our times. The Recruiting team is at the heart of this mission, tasked with identifying and hiring exceptional individuals who align with OpenAI's values and cultural ambitions. Our approach to recruitment aims to set the standard for excellence and innovation in the field, connecting outstanding candidates with opportunities to impact the future of AI. About the Role As a Senior Technical Sourcer at OpenAI, you will play a key role in identifying and engaging top-tier engineering talent across a broad range of technical domains. Your focus will be on sourcing exceptional software engineers and technical talent to help build world-class teams advancing our mission in AI research and deployment. In this role, you will: Lead sourcing strategies to identify and engage candidates across a variety of engineering disciplines, including software engineering, backend systems, product engineering, and related technical areas. Develop and maintain a strong pipeline of passive candidates through proactive outreach, research, and networking. Collaborate closely with hiring managers and technical leaders to deeply understand hiring needs and refine sourcing approaches accordingly. Leverage advanced sourcing techniques and tools to identify and attract exceptional talent. Represent OpenAI at industry events and conferences to promote our mission and connect with potential candidates. Maintain accurate and organized candidate data and metrics to inform sourcing strategies and decision-making. You might thrive in this role if you have: 5+ years of experience in technical sourcing, with a focus on engineering or technical roles. A proven track record of successfully sourcing candidates across a range of software engineering and

About the Team OpenAI’s Stargate and 3P Engineering teams are responsible for building and scaling the external infrastructure ecosystem that powers advanced AI systems. We work across hyperscalers, colocation providers, cloud partners, and strategic third-party operators to turn contracted capacity into production-ready compute. Our scope spans the full lifecycle of external deployments: commercial alignment, technical readiness, network integration, hardware enablement, operational readiness, and long-range scaling strategy. As OpenAI’s infrastructure footprint expands globally, we need leaders who can convert complex partner environments into reliable, high-velocity capacity for training and inference workloads. About the Role We are seeking a Technical Program Manager, Token-as-a-Service (TaaS) to lead delivery of external compute capacity that directly serves OpenAI model workloads. In this role, you will own complex cross-functional programs that transform third-party infrastructure into usable tokens at scale. You will partner across engineering, capacity planning, networking, hardware, finance, product, and external providers to ensure that deployed capacity translates into real production throughput. This role sits at the intersection of infrastructure execution, systems readiness, and business impact. Success requires strong technical fluency, elite program management, and the ability to drive accountability across internal teams and external partners. This is a high-visibility role with direct impact on OpenAI’s ability to scale model training and inference globally. This role is based in San Francisco, CA, with a hybrid work model of 3 days in office per week. Relocation assistance is available. Key Responsibilities Lead end-to-end delivery programs that convert external infrastructure capacity into production-ready token supply. Own readiness across compute, storage, networking, security, and operational dependencies for third-party environments. Build

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

About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. Make a Difference: Monitor and maintain deployed m

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: Notion’s Integrated Marketing team connects our brand story to the world—ensuring that every campaign, launch, and experience builds on global awareness of Notion as the intelligent, AI-connected workspace for modern work. We're looking for an experienced, creative, and rigorous brand campaign expert who excels at conceptualizing innovative campaign strategies and bringing clarity to complex challenges. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: The Campaign Manager, Brand brings Notion’s mission, product capabilities, and customer stories to life through targeted, insight-driven brand campaigns. This role is responsible for conceptualizing, developing, and executing integrated marketing programs that connect Notion’s core value props to the needs and aspirations of our customers—from individuals to global enterprises. Reporting to the Campaign Lead,

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: Notion is looking for an Early Career Recruiter who wants to reimagine what early career hiring can look like. This is a role for a builder: someone energized by the question of how to find and cultivate exceptional emerging talent, who gets excited about crafting programs and experiences that don't yet exist, and who sees employer brand, candidate experience, and assessment design in an AI era as creative problems worth obsessing over. You'll own Notion's early career strategy end-to-end alongside a team of talented teammates — from how we reach communities to how we evaluate potential, develop talent, and convert interns and new grads into the next generation of Notinos. You'll work closely with our Engineering, Product, Design, Sales, and People teams. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: A differentiated early career engine — design and run

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role Millions of people use Notion — and this number is increasing every day. That means millions of people, from students to large enterprises, trust us to keep their data secure and private, and we value this more than anything. We want to keep earning trust, while also continuing to amaze our users with the tools they can build in Notion. Notion is looking for software engineers who are excited to make trust and security a core part of how Notion scales. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve Build authentication and other product features that make Notion safe and secure by default, helping more people and teams trust Notion for their most important work while supporting growth across consumers and enterprise customers. Build scalable, AI-powered systems to detect, investigate, and mitigate risks across Notion, including phishing, spam, objectionable

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role You'll own the quality bar for Notion AI products. You’ll work with product and engineering teams to build systems to define what “good” looks like, measure our progress, and drive changes to deliver reliable and high-quality AI experiences. Your work directly shapes how Notion's AI products behave for millions of users. This isn't a traditional software engineering role. It’s an art & science role . You won't spend your days writing code. Instead, you'll focus on understanding and shaping how our AI products behave through context engineering, designing evaluation systems, and analyzing data. This team sits in our AI engineering team, working directly with engineering, product, design, and data. This role is a unique blend of ops, strategy, and product thinking. Day to day, you'll live in production data, ship prompt fixes, run evals and, in effect, shape our quality strategy. As part of that you'll shape Notion's model strategy and work directly with frontier AI labs (OpenAI, Anthropic, Google) to evaluate and launch new models. We're looking for problem-seeking generalists interested in 0 → 1 : curious people wi