Partner Development Director in United States

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, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, meas

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 might Create ambitious RL environments to push our models to their limits, and measure frontie

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 We believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). 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 that improve scaling of compute on context. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures,

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 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 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 The Support Automation team at OpenAI scales the organization by applying cutting-edge AI models to real-world challenges, automating and enhancing work across the organization. From customer operations to engineering, we develop an ecosystem of automation products that empower our colleagues and drive impact. We're passionate about crafting products that serve those around us, blending rapid prototyping with a focus on long-term quality and reliability. By creating reusable solutions, we create patterns that can be applied across diverse domains within OpenAI. TLDR: this team leverages OpenAI technology to improve OpenAI, and you’ll have the opportunity to leverage the full extent of our tech (both public and pre-released) to accomplish this mission. About the Role We’re looking for a Backend Software Engineer with experience working in ML/LLM-heavy domains to help to design and build an evals infrastructure that measures the quality of OpenAI’s support automation. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. The role will especially focus on working closely with Data Science and Research partners to design and build evals at scale. In this role, you will: Design eval pipelines that are reliable, reproducible, and extendable Build the infrastructure for continuous eval monitoring frameworks (regression/drift monitoring, building robust golden datasets) along with feedback loops that ultimately strengthen support automation Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows. Collaborate closely with data, research, and engineering teams to integrate OpenAI models into high-leverage workflows

About the Team The Codex Research 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 the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measu

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 are seeking a Operations Program Manager (OPM) to serve as the single-threaded operational leader for new hardware introductions (NPI) and production ramps across OpenAI’s AI infrastructure systems. This role combines hands-on execution with strategic ownership. You will be responsible for defining the operating model, aligning cross-functional stakeholders, setting the critical path, making informed tradeoffs, escalating decisively, and ensuring hardware programs deliver on schedule, quality, cost, and scalability. Success in this role requires comfort operating in ambiguity, influencing without authority, and driving alignment across internal teams and external partners—while keeping eyes firmly on long-term system scalability and repeatability. In this role, you will: Strategic & Leadership Ownership Act as the single-threaded owner for operational readiness across NPI and ramp, accountable for outcomes from early bring-up through sustained production Translate OpenAI’s infrastructure strategy and engineering objectives into clear operating plans, execution priorities, and decision frameworks Drive alignment across Engineering, Operations, Strategic Sourcing, Finance, Capacity Planning, and Executive stakeholders by framing tradeoffs, risks, and recommendations Proactively identify inflection points where decisions or investments are required to protect long-term scale, reliability, or cost targets Influence operational strategy with manufacturing par

About the Team OpenAI’s Applications Engineering organization builds and operates the products that bring our cutting-edge research to millions of users and developers worldwide. The Applied Foundations team owns the core product and platform layers that make those experiences possible — from identity & access, to safety to payments & commerce across all of our apps. Our teams span product engineering, infrastructure, and safety, working together to deliver technology that is reliable, secure, and trusted at global scale. About the Role You will be a Senior iOS engineer on OpenAI’s Applied Foundations team, building the core mobile experiences that power how users sign up, manage their account, family features, pay for services, stay safe, and interact with OpenAI’s products with confidence. This role is about creating high-quality products as well as reusable iOS foundations that product teams across different OpenAI apps depend on to ship quickly while meeting the highest standards for security, reliability, and user trust. You’ll own complex client-side systems spanning UI, networking, local state, payment integrations and Apple platform integrations, and work closely with backend, product, and safety partners to shape the architecture that supports OpenAI’s mobile ecosystem at global scale. In this role, you will: Build and ship new experiences on iOS that showcase the power of AI. Optimize app performance, reliability, and responsiveness at global scale. Design and maintain shared iOS frameworks and primitives for account, trust, and commerce flows that are used across OpenAI’s mobile apps. Establish robust testing frameworks and refine app architecture for long-term maintainability. Collaborate with product, design, research, and backend teams to deliver high-impact features. Provide technical leadership to shape the future of OpenAI’s iOS platform. You might thrive in this role if you: Have 4+ years of professional software engineering experience. Hav

About the Team The Agent Enablement team works across engineering, product, design, and research to bring our technology to the world. We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, and platform barriers. Our commitment is to facilitate the use of AI to enhance lives, supported by rigorous insights into how people use our products. About the Role We are looking for experienced full-stack engineers to join our new Agent Enablement team. Our goal is to design and grow an open ecosystem of agent-enabled sites and services. This is a wide-ranging role: you’ll build new user and agent identity protocols, user experiences to control and observe agents across web, desktop, and mobile, and much more. We will rely on you to drive our technical decisions while also steering our product and partnership direction, optimizing for both short-term impact and long-term success of the ecosystem. We value engineers who are impact-driven, autonomous, and adept at removing barriers to forward progress. In this role, you will: Design the primitives and protocols for an open agent ecosystem, enabling our users’ agents to make the best use of sites and services across the internet. Build a next-generation user experience to observe and control agents, across web, desktop, and mobile. Evolve our approach to token consumption across subscriptions and API customers. Execute on fast-paced projects in collaboration with research, design, data science and other product engineering teams. Work closely with our strategic customers and partners to grow the ecosystem. You might thrive in this role if you: Have strong full-stack engineering skills and experience shipping customer-facing products from concept to production. You’re comfortable working across frontend, backend, APIs, data models, and product desig

About the Team: The OpenAI API team builds the foundation that enables every developer to harness OpenAI’s models safely, reliably, and at scale. We design and operate the systems that power model serving, API access, billing, developer tooling, and enterprise integrations—forming the connective tissue between OpenAI’s research breakthroughs and real-world products. Our mission is to make it effortless for anyone to build with OpenAI technology. We’re responsible for the infrastructure and product layers that allow millions of developers to integrate GPT models, fine-tune behavior, manage data, and deliver transformative experiences to their users. We collaborate across product, research, and engineering teams to ensure that innovation in model capabilities translates directly into value for customers. The API team spans multiple disciplines, including product management, infrastructure engineering, developer experience, and data systems. We care deeply about reliability, scalability, and simplicity—creating tools that let developers focus on their ideas while we handle the complexity of running world-class AI systems. About the Role: We are seeking an experienced Product Manager to define and scale the construction of our data processing, data privacy, billing, and access controls products. You will set strategy and execute on projects like expanding our regional data processing footprint, enabling new inference caching controls in the API or building APIs that make it easier for organizations to manage their spend limits. You will also define the strategy and ship foundational capabilities that ensure customers use OpenAI products securely, privately, and with enterprise-grade controls. This role partners deeply with engineering, security, legal, compliance, finance and leadership to deliver high-trust, enterprise-grade systems. 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 n

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 every day, and we’re growing quickly. The Infrastructure Security team’s mission is to build a secure-by-default foundation across Notion’s technical stacks—architecting systems that make the secure path the easy path. As an IC4 on this team, you’ll own meaningful infrastructure security problems end-to-end: from identifying risk, to designing pragmatic controls, to shipping secure defaults that scale across engineering. 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: Proactively enhance the security posture of our AWS accounts and cloud infrastructure. Create secure frameworks for secrets management and authentication/authorization. Design and deploy robust Identity and Access Management (IAM) solutions. Provide guidance and education on security and privacy best practices to cross-functional partners. Participate in (and hel

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: We’re looking for a Marketing Strategy & Operations Manager based in San Francisco or New York. This person will be the operational backbone of Marketing builds, launches, and measures campaigns, and how leads/accounts are routed, and managed. You'll own the end-to-end of campaign services across templates, QA, deliverability, and execution. You’ll also play a role in the monitoring, debugging and managing any MQL/MQA issues (from creation to handoff to Sales) as they arise. You'll work across many teams across multiple regions (EMEA, AMER), partnering closely with Marketing, SDR leadership, and our agency partners to build scalable processes and tooling that increase pipeline throughput and campaign quality. If you thrive on building systems that bring order to complexity and love bridging the gap between Marketing and Sales, this role is for you. What You'll Achieve: Campaign Operations Establish and maintain campaign templates, standardized QA processes, and reusable campaign architecture in Marketo, customer.io and SFDC. Own the Campaign object in SFDC — including campaign member status designations, naming co

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: We’re looking for a Technical Enablement Manager to own the end-to-end learning, knowledge, and training experience for Notion’s global customer experience (CX) teams—spanning onboarding, change management, and continuous learning. This is an opportunity to build, lead and innovate on programs that ensure customer-facing support teams have the knowledge, skills and processes they need to consistently deliver high-quality support experiences to Notion customers. You’ll set the enablement strategy, partnering closely with CX leadership and cross-functional partners to identify skill, knowledge and process gaps, and translate those needs into durable enablement solutions—content, workflows, and programs. This role is based in New York City, USA. 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: Own end-to-end CX enablement for a business vertical: define learning outcomes, readiness expectations, and content strategy across