Technical Services Manager in San Francisco

About the Team: The OpenAI API team builds the foundation that enables every developer to harness OpenAI’s models safely, reliably, and at scale. Our mission is to make it effortless for any developer to build transformative products with OpenAI’s models. We’re responsible for the infrastructure and product layers that allow millions of developers to integrate our models, fine-tune behavior, manage data, and deliver experiences to their users. We collaborate deeply across product, research, and engineering teams to drive innovation at the model layer and then directly translate that into value for customers. About the Role: As the Agents Product Manager for the API team, you'll be at the forefront of defining and guiding the future of how developers build agentic applications on top of our AI models. You’ll set clear priorities and drive impactful improvements to model capabilities, balancing user needs, safety considerations, and technical innovation. This role is perfect for a proactive, technically adept PM who thrives on solving challenging, ambiguous problems through structured product thinking and close collaboration with customers, engineers, and researchers. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Deeply understand problems faced by agent builders and identify opportunities where our products and models can make building agents faster, more intuitive, more reliable, and more powerful. Define strategic priorities and roadmap for improving agentic infrastructure for API users, focusing on user outcomes and emerging capabilities. Partner with research and engineering teams at a technical level to translate those priorities into developer products and features (SDKs, APIs, and more). Deliver quickly while maintaining a high bar for product quality and user experience. You might thrive in this role if you: Have 5+ years of product management or related industry experience. Proven track record of b

About the Team Like every team at OpenAI, the Marketing team contributes to our broader mission of ensuring responsible and widespread adoption of artificial intelligence. With that aim in mind, we are responsible for developing and executing strategies that drive awareness, engagement, and usage for OpenAI’s products and platform amongst our core audiences. Our focus extends beyond just promoting product features; we aim to provide valuable insights and resources that help our users make the most out of AI technologies. The Marketing Insights & Analytics team aims to understand the markets, audiences, behaviors, attitudes and needs to shape outreach strategies and inform product and business decisions. We’re the strategic partner that discovers insights, specifically: foundational understanding, marketing strategy, thought leadership, measurement and tracking. About the Role You will be the Market Research Lead that translates insights into actionable marketing plans and executions, drive business results, and orient the team towards strategic thinking to drive brand outcomes. This is critical as we hope to reach millions of users and businesses worldwide. This role can be based in San Francisco, CA or NYC, NY utilizing a hybrid work model (3 days per week in-office). In this role, you will: Play an integral part of Marketing and be a strategic partner to brand, product marketing, creative, product and beyond. Design, execute, and deliver high-impact research using mixed methods. Work on a diverse portfolio of business challenges - how do we reach the next billion people, how do we grow internationally, how do we position our suite of products, and how do we ship joy to our customers. Translate business questions into research plans. Translate data into clear, compelling narratives. Develop deep empathy for developers, builders, and technical decision-makers, understanding their workflows, motivations, and pain points across the lifecycle Shape go-to-market str

About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the Role Our GTM team is uniquely positioned to help customers realize the transformative potential of advanced AI models for their businesses and end users. As part of the GTM Strategy & Operations team, you’ll play a critical role in guiding the GTM strategy and driving the operational efficiency to accomplish this mission. This role serves as a trusted advisor to GTM leadership—providing data-driven insights, managing core operating cadences, and leading high-impact projects that influence how we engage with customers and scale our business. You’ll collaborate cross-functionally with Finance, Enablement, Data and Growth Strategy teams to align efforts, drive efficiencies, and accelerate growth. This role is a central role, meaning it is not tied to a specific business partner, but rather designing the global processes for the business. In this role, you'll: Design, build, and manage our operating rhythms (Forecasting, Pipeline Council, Big Deal Reviews, and MBRs/QBRs). Conduct strategic analyses to determine trends and identify opportunities for process and strategy optimization Collaborate with GTM leadership and cross-functional stakeholders to develop go-to market strategy and resource plans Lead strategic projects to improve efficiency and effectiveness across the revenue organization. Partner closely with technical teams to impl

About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with

About the Team The Personalization-Memory team, within OpenAI's broader Personal AGI organization, is focused on developing agents that can learn from prior interactions in order to become more helpful and efficient over time. We build general-purpose memory and personalization capabilities that transfer across ChatGPT and other agentic products, and we collaborate with applied engineering on the product surfaces that allow users to interact with memory. About the Role As a Research Engineer / Research Scientist on the Personalization-Memory team, your work will span memory architecture, post-training, and developing long-horizon tasks for training and evaluations. We're looking for individuals who have a background in reinforcement learning research, are able to iterate quickly, and who can convert scientific rigor and long-term research into realized product impact. 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: Own and pursue a research agenda for improving long-horizon memory and personalization in frontier models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. Collaborate closely with the research and product teams to influence the shape of technical solutions in the product. You might thrive in this role if you: Love being on the cutting edge of RL and frontier model research. Value principled approaches and research craftsmanship. Are passionate about long-horizon tasks, memory, and turning your research into product impact. Are comfortable diving into a large ML codebase to debug. Thrive in a fast-paced, dynamic, and technically complex environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI syst

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions optimized for advanced AI workloads. We collaborate across research, software, and external hardware partners to design and deploy next-generation AI systems at scale. Our team works closely with silicon vendors and system partners to evaluate emerging technologies, validate performance characteristics, and ensure that hardware capabilities translate effectively to real-world AI workloads. About the Role We are seeking a 3P Hardware Architecture Expert with deep expertise in GPU and accelerator architectures to engage directly with silicon vendors and guide hardware decisions for AI infrastructure. In this role, you will evaluate architectural tradeoffs across compute, memory, and interconnect systems, translating vendor specifications into real-world workload impact. You will play a critical role in early silicon evaluation, benchmarking, and performance validation, helping ensure that next-generation hardware meets the needs of our workloads. This role is highly hands-on and requires both deep technical understanding and the ability to engage at a high level with partners such as NVIDIA and AMD on architectural direction and design tradeoffs. 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. Key Responsibilities Engage deeply with silicon vendors (e.g NVIDIA & AMD) on GPU and accelerator architecture tradeoffs. Analyze and interpret performance, power, and efficiency characteristics of next-generation hardware. Translate vendor specifications into expected real-world performance for AI workloads. Evaluate architectural aspects including: compute throughput and utilization memory systems (HBM, cache hierarchies, bandwidth constraints) data types and precision tradeoffs (FP16, BF16, FP8, etc.) interconnect and scaling behavior. Run benchmarks and profiling to validate hardware performance a

About the team OpenAI’s Education team is building products and experiences that help learners, educators, and institutions benefit from AI in ways that are rigorous, useful, and grounded in real learning outcomes. The work spans both consumer and B2B education, with close collaboration across engineering, learning science, design, data, and research. This team sits in a highly strategic investment area for OpenAI, with strong opportunities to shape how product ideas flow across consumer and institution-facing experiences. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the role We’re looking for a product-minded Full Stack Engineer to help build OpenAI’s education products from the ground up. You’ll own end-to-end development across the stack, from early concepting and prototyping through production launch and iteration. This is an opportunity to work on a highly strategic, early-stage product area where engineering judgment, product sense, and customer empathy all matter. You’ll partner closely with leaders across the education org, including learning scientists, researchers, designers, and cross-functional partners, to turn emerging ideas into durable product experiences for schools, universities, and other education stakeholders. In this role, you will: Build and ship product experiences across the full stack for OpenAI’s education offerings Own projects end-to-end, from ideation and technical design through implementation, launch, and iteration Work closely with learning scientists and researchers to translate learning goals and evidence into product decisions Collaborate with design, data, and cross-functional partners to build thoughtful, high-quality user experiences Help define the engineering foundation for a growing education pod, including patterns, systems, and technical

About the Team The Artifacts team is building the AI-native creation layer for documents, spreadsheets, slide decks, dashboards, reports, analyses, and new forms of interactive work products. We are rethinking what creation looks like when models can move from an ambiguous user goal to a polished, editable artifact with strong structure, taste, correctness, and speed. This is a high-agency team working across product, infrastructure, and research. We partner closely with model training teams to shape how frontier models create artifacts, and with ChatGPT product teams to turn those capabilities into experiences that millions of people can use. The work spans full-stack product engineering, model integration, rendering and editing systems, collaboration, storage, evaluation loops, and production reliability. Our ambition is to build the premier product experience for AI-generated artifacts: starting with familiar work products like slides, sheets, and docs, then expanding into new artifact types that are only possible in an AI-native world. About the Role As Engineering Manager, Artifacts, you will lead and grow the engineering team responsible for building this product and technical foundation. You will manage a team of full-stack and infrastructure-oriented engineers, set technical direction, and stay hands-on enough to shape architecture and debug hard problems. This role sits at the intersection of product engineering, research, and infrastructure. You will partner with researchers on how models are trained and evaluated for artifact creation, with product and design on the user experience. This is a strong fit for a technical manager who wants to build and ship, not only coordinate. The team has a fast trajectory, so you will help define both the product surface and the team that builds it. In this role, you will: Lead, manage, and grow a team building AI-native artifact creation experiences across documents, spreadsheets, slide decks, and emerging artifact form

About the Team We’re hiring software engineers to make OpenAI’s Model Performance teams more productive. These teams work on the systems, tooling, and infrastructure that help improve model performance across OpenAI’s training and inference workloads at frontier scale. About the Role We’re looking for an autonomous, high-ownership developer productivity engineer who cares deeply about helping other engineers move faster, safer, and with more confidence. This role will sit within OpenAI’s Model Performance organization, contributing to developer infrastructure, CI systems, testing workflows, tooling, and broader performance infrastructure efforts. There is also a strong opportunity to contribute to the Triton project and help improve the systems that support performance-critical engineering work across OpenAI. In this role you will: Improve development workflows for engineers working on model performance infrastructure Design and improve CI/CD, release, validation, and testing pipelines Build and maintain tools that improve reliability, iteration speed, and engineering confidence Partner closely with engineers to identify friction in testing, debugging, deployment, and development workflows Contribute to infrastructure efforts that support performance-critical training and inference systems Help improve developer experience across Python-heavy codebases and performance-oriented infrastructure Work in a high-context, ambiguous environment where ownership and good judgment matter You might thrive in this role if: You are motivated by enabling the people around you and helping engineers do their best work You have strong experience with CI/CD, developer infrastructure, testing systems, tooling, or build/release workflows You are highly collaborative, empathetic, and comfortable partnering deeply with technical teams You are strong in Python and enjoy building reliable, scalable developer tools and infrastructure You have experience improving large-scale engineering work

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with research, software, and external hardware partners to shape the next generation of AI systems, from silicon through full-scale deployments. Our team focuses on understanding and optimizing performance across the full system stack—ensuring that architectural decisions are grounded in rigorous, quantitative analysis of real-world workloads. About the Role We are seeking a Performance Modeling Lead to build and lead a small, high-impact team responsible for answering forward-looking architectural questions across AI infrastructure systems. You will develop modeling frameworks and methodologies to evaluate system-level tradeoffs and guide key design decisions. Your work will directly influence reference architectures, vendor designs, and long-term infrastructure strategy. This role sits at the intersection of AI workloads, system architecture, and quantitative modeling, and requires strong technical judgment, ownership, and the ability to translate complex analysis into clear, actionable guidance. 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. Key Responsibilities Build and own a performance modeling framework/toolchain to evaluate AI systems across multiple levels of abstraction. Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology. Develop performance models to guide decisions on: scale-up vs. scale-out architectures interconnect and network design memory hierarchy and system balance. Translate modeling outputs into clear recommendations for internal teams and external hardware vendors. Influence reference designs and vendor roadmaps through data-driven insights. Partner closely with machine learning, systems, and hardware teams to understand workload characte

About the Team OpenAI’s GTM Partnerships team builds a strategic, global partner ecosystem designed to accelerate customer success, enable enterprise AI adoption, and drive durable growth in support of OpenAI’s mission. We work closely across Product, Research, Sales, Legal, Communications, and regional leadership to ensure a cohesive strategy and disciplined execution with our most strategic partners. About the Role We are hiring a Partner Director, Global McKinsey Alliance to lead and scale OpenAI’s relationship with McKinsey & Company. This role will serve as the single accountable executive owner of the alliance globally. You will define the partnership strategy and operating model, translating executive alignment into scaled commercial and transformation outcomes across regions and industries. You will work closely with McKinsey’s global leadership, industry and functional practices, and technology organizations—including QuantumBlack, AI by McKinsey—to develop differentiated enterprise AI offerings, pursue complex transformation opportunities, and help customers move from strategy to production deployment and measurable value. The role carries responsibility for the health, performance, and long-term expansion of the partnership. Success requires senior executive presence, sound judgment, commercial discipline, technical fluency, and the ability to operate effectively across a complex, partner-led organization. In this role, you will: Own the global McKinsey relationship, including alliance strategy, pipeline growth, enterprise impact, deployment scale, and long-term expansion across priority industries. Define and run the partnership’s operating model across executive governance, joint planning, regional execution, opportunity management, resource allocation, and escalation. Serve as OpenAI’s senior executive counterpart to McKinsey’s global leadership and relevant industry, functional, technology, and regional leaders. Develop a differentiated alliance s

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 an experienced SoC Architect to lead the definition and development of next-generation custom AI silicon for edge deployments. This role will be responsible for shaping the architecture of highly efficient, high-performance SoCs optimized for machine learning inference and on-device intelligence. You will work cross-functionally with internal engineering teams and external ecosystem partners to translate product requirements into scalable silicon solutions, driving execution from concept through delivery. In this role you will: Define the architecture and technical roadmap for custom SoCs targeted for edge applications. Drive system-level tradeoff analysis across compute, memory, interconnect, power, thermal, and cost constraints. Architect energy-efficient ML compute subsystems optimized for inference workloads and real-world deployment environments. Collaborate with internal hardware, software, systems, and product teams to align architecture with platform needs. Partner with external silicon vendors, IP providers, and manufacturing partners to execute development plans. Lead hardware/software co-design efforts to maximize performance per watt and end-to-end system efficiency. Guide implementation teams through microarchitecture, RTL development, validation, and bring-up phases. Operate effectively in agile development environments and help teams deliver against aggressive schedules and milestones. You might thrive in this role if: Proven exper

About the team Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role The stakes of securing OpenAI increases as our internal coding and research becomes increasingly driven by autonomous AI agents. Compromising these agents could allow a cyber threat actor to compromise many other parts of the company. In this role, you would lead Preparedness work defending the security of our internal AI agents against insiders, Advanced Persistent Threats (APTs), or powerful AI agents. We’re looking for a strong hands-on technical executor with experience working directly with advanced cyber threat actors. In this role, you will: Develop and maintain threat models via which advanced attackers could compromise our coding assistants and automated security systems. Identify security investments that are especially critical to make in advance; for example, prioritizing by implementation lead-times, costs, and benefit. Partner with Security, Infrastructure, Research, Legal, and Preparedness to align on implementation plans and tradeoffs. Lead technical execution directly when needed, including prototyping controls, writing and reviewing software, and coordinating engineers across teams. Work with penetration testers to close gaps in defenses. You might thrive in this role if you: Are an exceptional hands-on technical executor. Have worked with advanced

About the Team The Demo Studio is responsible for translating OpenAI’s most advanced capabilities into tangible, high-impact experiences for customers. We design and deliver the demos, applications, and environments that define how executives understand what is possible with AI. Our work sits at the intersection of product, engineering, design, and go-to-market. We operate as a hybrid of product studio and live production team, building experiences that are both technically credible and narratively compelling. About the Role We’re looking for a Demo Studio Lead to own the end-to-end demo experience for OpenAI’s major events, webinars, and strategic programs. This is a highly cross-functional role focused on translating cutting-edge AI capabilities into clear, compelling, and production-ready experiences. You will own the full demo portfolio for an event or initiative, spanning mainstage moments, breakout experiences, booths, and supporting content. You’ll define the narrative, architect workflows, build high-fidelity demo environments, direct presenters, and ensure flawless execution in live environments. This is not a traditional sales engineering, presentation, or narrowly scoped design role — it requires a combination of product thinking, technical fluency, storytelling, systems design, and operational excellence. A key part of the role is presenting the work directly: delivering live demonstrations to executive, technical, and industry audiences across mainstage, breakout, customer, and recorded settings. This role is ideal for someone who thrives in ambiguity, operates with strong ownership, and is excited about shaping how the world experiences AI firsthand. This is a hybrid role that can be based in either San Francisco or New York. In this role, you will: Own the end-to-end demo experience across OpenAI-hosted summits, webinars, third-party industry events, and strategic executive demonstrations. Translate approved product positioning, real OpenAI capabiliti

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