Engineering Manager Jobs

About the Team The Ads Support Delivery team is responsible for helping successfully operate and grow on our Ads product. This includes technical guidance, troubleshooting complex delivery and monetization issues, and partnering closely with Product, Engineering, Trust & Safety and Go-To-Market teams to resolve customer-impacting problems and improve the platform over time. The team’s mission is to deliver a high-quality customer experience at scale by combining strong human support with automation, self-service, and AI-enabled workflows, while maintaining high operational rigor. About the Role: As a Support Delivery Lead for Ads, you will lead a team responsible for end-to-end support delivery across the ads ecosystem, including campaign setup, delivery, billing, measurement, and policy navigation. You will set the operational bar for quality, responsiveness, and consistency; coach and grow the team; and translate support signals into actionable improvements with Engineering, Product, and Go-To-Market partners. 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 and support a team of Ads support engineers, ensuring they have the tools, clarity, and coaching needed to operate at a high bar in a technically complex domain. Set clear expectations and operating standards, run recurring performance reviews, and build development plans that grow both technical depth (ad tech fluency) and customer-facing excellence. Design and continuously improve support coverage for ad buyers, ensuring the team can diagnose delivery issues and monetization and integration issues with equal rigor. Act as the bridge between Support Delivery, Engineering, Product, and Go-To-Market teams. Drive alignment on priorities, escalation paths, launch readiness, tooling improvements and mechanisms to reduce repeated customer pain points. Partner with engineering teams

About the Team The Pricing & Monetization team is responsible for how our products create and capture value. We partner closely with Product, Engineering, Data Science, GTM, and Finance to design pricing models, packaging, and commercial strategies that support adoption, growth, and long-term scaling of the business. To thrive in this team, you need to be a proactive problem-solver who excels at bringing structure to ambiguous challenges. Our work demands strategic thinking, cross-functional collaboration, and precision in execution. Team members succeed when they are analytical, detail-oriented, skilled at balancing multiple priorities, and passionate about driving high-stakes projects forward to deliver meaningful results. About the Role We are looking for a Pricing Strategist to shape how we price and monetize OpenAI’s API platform. You’ll own the end-to-end pricing strategy across model launches, price architecture, packaging, commitments and discounts, and monetization guardrails. You’ll work closely with senior leaders across Product, Engineering, Data Science, GTM, and Finance to define pricing approaches, improve commercial decision-making, and bring more rigor to how we monetize our API offerings. You should be comfortable building monetization frameworks and commercial policies, analyzing tradeoffs, supporting high-impact decisions and driving decision making. You should also care deeply about the customer perspective and believe that strong pricing reflects a real understanding of customer value, needs, and friction points in order to build pricing that is clear, fair, and aligned with how customers experience our products. This role will report to the Head of Product Pricing for API & Platform. What you’ll do Develop the end-to-end pricing strategy for our API platform, including model launch pricing, price architecture, packaging, discount logic, and monetization guardrails. Recommend pricing for new models, capabilities, and platform offerings,

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. We work closely with hardware design teams, manufacturing partners, suppliers, and data center operations to deliver the compute platforms that power frontier AI. The Manufacturing Engineering team ensures our hardware can be built, tested, deployed, and supported at hyperscale. We bridge Hardware Engineering, Quality, Supply Chain, Contract Manufacturers, and Hardware Operations to continuously improve manufacturing performance throughout the product lifecycle. As our fleet grows globally, sustaining manufacturing engineering becomes increasingly important to maintain product quality, improve manufacturability, and rapidly resolve production issues. About the Role We are seeking a PCBA Manufacturing Engineer (Sustaining) to support production and continuous improvement of printed circuit board assemblies (PCBAs) used throughout Industrial Compute hardware platforms. This role focuses on sustaining engineering after product launch. You'll partner closely with Hardware Design, Quality, Manufacturing, Test Engineering, Supply Chain, and our contract manufacturers to resolve production issues, improve manufacturing yield, reduce failures, implement engineering changes, and ensure stable high-volume manufacturing. The ideal candidate has experience supporting complex server, networking, accelerator, storage, or high-performance electronics manufacturing environments. Key Responsibilities Own sustaining manufacturing engineering for PCBA production across multiple hardware platforms. Drive root cause investigations for manufacturing defects, field failures, and production escapes. Partner with Hardware Design Engineers to improve manufacturability (DFM/DFA/DFT). Support engineering change orders (ECOs) and manufacturing change implementation. Work directly with contract manufacturers to improve production yield, cycle time, and quality. Analyze manuf

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside our cloud partners, infrastructure providers, and internal engineering teams, we operate hyperscale AI campuses that support the training and deployment of frontier AI models. The Site Operations team serves as OpenAI's on-site operational presence, helping ensure campuses operate safely, efficiently, and in alignment with Industrial Compute standards. We work closely with Hardware Operations, Infrastructure Delivery, Network Operations, Security, Facilities, Construction, and our infrastructure partners to support day-to-day site execution and maintain operational readiness. As Industrial Compute continues to expand globally, Site Operations plays a critical role in ensuring each campus is prepared to support reliable AI infrastructure at scale. About the Role We are seeking a Site Operations Technician to support the daily operation of Industrial Compute campuses. This role acts as OpenAI's on-site technical representative, helping coordinate activities across hardware operations, facilities, construction, logistics, security, and external service providers. You will perform routine site inspections, support asset tracking, coordinate vendor activities, assist with operational readiness, document site conditions, and help ensure infrastructure issues are identified and resolved quickly. The ideal candidate enjoys working in highly technical environments, is detail-oriented, and thrives in fast-paced operational settings where no two days are the same. Key Responsibilities Perform routine walkthroughs of Industrial Compute facilities to verify operational readiness and identify potential issues. Monitor site conditions and report abnormalities involving hardware spaces, network rooms, utilities, logistics areas, and common infrastructure. Support coordination of vendors, contractors, and partner organizations performing work o

About the Team The GTM Data Science team partners with Go-to-Market, Technical Success, Product, Engineering, RevOps, and Strategic Finance to build the shared intelligence layer for OpenAI's B2B business. The team turns product usage, customer behavior, revenue, field activity, and customer feedback into rigorous insight products that help leaders and field teams understand where customers are succeeding, where adoption is blocked, and what actions will accelerate durable growth. We are building systems that make customer intelligence proactive: surfacing risk, expansion potential, product gaps, and repeatable playbooks before they show up as escalations or missed opportunities. About the Role As the Applied Data Science & Insights Lead for GTM Intelligence Solutions and Technical Success, you will be a hands-on technical leader responsible for shaping how OpenAI measures, understands, and improves customer adoption across our B2B products. You will build AI/ML-powered intelligence products that connect account health, product usage, customer lifecycle, support tier, qualitative sentiment, commercial context, and field actions into a practical operating system for GTM and Technical Success. This role will build the data science foundation for Technical Success: defining the metrics, models, operating insights, and decision systems that help the team scale customer adoption and expansion with rigor. You will also be expected to build and lead a small mighty team over time: setting direction, hiring and developing talent, creating operating cadences, and holding a high bar for technical rigor and business impact. You will lead the development of models, metrics, and decision systems that recommend what GTM and Technical Success teams should do next, explain why, and measure whether those interventions worked. Your work will help customers move from pilots to production, deepen usage across products, identify high-value use cases, reduce churn risk, and create a f

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. Role Overview We are seeking a Package Reliability Engineer to lead reliability engineering for advanced packages used in high-performance AI and computing systems. The primary focus of this role is to assess package level mechanical and thermal reliability risks and apply thermal and mechanical modeling to optimize package design, material selection, and assembly processes. The engineer will also develop reliability test plans with external partners, identify failure mechanisms, perform root-cause analysis, and recommend practical corrective actions. In this role, you will assess package reliability risks from early architecture development through product qualification and high-volume manufacturing. You will work closely with package design, silicon design, system engineering, manufacturing, and ASIC partners to predict package behavior, develop qualification strategies, resolve reliability issues, and improve overall package robustness and lifetime. In this role you will: Lead reliability test plan and assessments for advanced HPC packages, including risk identification, potential failure-mechanism analysis, root-cause investigation, mitigation planning, and corrective-action development. Drive reliability-focused package design optimization based on thermo-mechanical modeling to improve package reliability, power integrity, thermal performance, mechanical robustness, and platform scalability. Develop, validate, and apply package reliability models and lifetime-prediction

About the team The Technical Success team is responsible for ensuring the safe and effective deployment of ChatGPT and OpenAI API applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, ensuring developers and enterprises maximize value from our models and products. The Ecosystem team builds and scales third-party integrations around ChatGPT and Codex. We work across product, engineering, partnerships, safety, legal, policy, and go-to-market to create integrations that are useful, trustworthy, and technically sound. About the role We’re looking for an Applied Deployment Engineer to help build and deepen ChatGPT integrations with third-party messaging platforms. The initial focus will be on partner work as well as future opportunities with other messaging apps around the world. This is a hands-on, partner-facing engineering role. You’ll work closely with external product and engineering teams to improve existing integrations, expand capabilities such as image generation, increase retention, and translate partner needs back into OpenAI’s product and engineering roadmap. You should be comfortable writing code daily, making changes across platform or monorepo surfaces when needed, and moving fluidly between technical discovery, product tradeoffs, prototyping, debugging, and executive-level communication. This role is best suited for a strong product-minded engineer with excellent communication skills, sound technical judgment, and the ability to work across cultures, time zones, and organizations. This role is based in our San Francisco office. 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: Partner with messenger app product and engineering teams to design ChatGPT-powered experiences that fit naturally into chat, group, contact, and app-tab surfaces. Deepen existing partner integrations, with an initial focus on improving user ex

About the Team The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the Role We are hiring a Staff-level Data Scientist to help lead the evolution of OpenAI’s core experimentation platform. This role is focused on improving the statistical rigor, reliability, and practical usability of experimentation across the company. You’ll work on some of the hardest problems in online experimentation: sample ratio mismatch detection, variance reduction, bias mitigation, metric design, triggered analysis, heterogeneous treatment effects, sequential testing, and experimentation in complex ML systems. You’ll also help translate advanced statistical concepts into pragmatic systems and product experiences that teams can actually use. This is a highly technical individual contributor role with significant influence across methodology, platform architecture, and experimentation best practices. The ideal candidate combines deep statistical expertise with strong systems intuition and hands-on experience building or operating experimentation platforms at scale. In this role, you will: Drive the statistical direction and technical strategy for OpenAI’s experimentation platform Design and improve experimentation methodolo

About the Team Our Applied team brings OpenAI technologies to consumers and businesses around the world. We collaborate across research, engineering, design and business functions to turn cutting-edge AI advancements into impactful real-world applications. Our team has been behind notable product launches ( ChatGPT , API , Sora ), creating tools that help developers write code, enable businesses to operate more efficiently, and empower individuals to learn and create. As AI capabilities rapidly evolve, we focus on ensuring that our products are safe, accessible, and beneficial to all. About the Role As a Data Scientist on the Applied Product team, you will contribute to a data-driven product development culture for consumer and enterprise products at OpenAI. This is critical as our products reach millions of users and businesses worldwide. We are focused on aligning both research and product development to drive measurable impact for these individuals and organizations alike. You should expect to define our north-star metrics, design A/B tests, and establish source-of-truth dashboards that the entire company can use to answer their own product questions. Most importantly, you should expect to be a core member of the product development team. This role is based in San Francisco, CA or Seattle, WA. 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: Embed with the product development team as a trusted partner, uncovering new ways to improve the product and drive growth Define and interpret A/B tests that help answer critical questions about the impact of model and UX changes to our product Establish a data-driven product development culture by defining, tracking, and operationalizing feature-, product-, and company-level metrics Develop and socialize dashboards, reports, and other ways of enabling the team and company to answer product data questions in a self-serve way You might thrive

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a Senior Actuator Design and Integration Engineer to lead the development of custom electromechanical actuators for advanced robotic systems. You will own actuator development from early architecture and concept generation through prototype validation and system integration, partnering closely with mechanical, electrical, controls, firmware, reliability, and manufacturing teams. This role focuses on the design, integration, and validation of precision electromechanical systems, including motors, transmissions, sensing, structural components, and thermal architectures. You will help drive actuator development across the full engineering lifecycle while establishing scalable design, test, and integration practices for future robotic platforms. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Lead the architecture, design, and integration of custom robotic actuators, including motors, transmissions, sensing, thermal systems, structural components, and packaging. Define actuator requirements and system-level trade studies around torque density, bandwidth, efficiency, thermal performance, backdrivability, inertia, reliability, manufacturability, and cost. Design precision electromechanical assemblies with strong attention to tolerances, alignment, load paths, thermal expansion, sealing, wear, and serviceability. Drive actuator integration into robotic systems, partnering closely with controls, firmware, electrical, and robotics software teams to optimize closed-loop pe

About the Team The Corporate Development team sits at the intersection of OpenAI’s strategy and the global AI ecosystem. Partnering closely with research, engineering, product, GTM and business leaders, we analyze markets, technologies, and companies to identify opportunities that accelerate OpenAI’s mission and long-term strategy. Bringing together expertise in strategy, M&A, and integration, the team leads the end-to-end process of sourcing, evaluating, negotiating, and integrating acquisitions and other strategic transactions. About the Role This is a high-visibility, strategically critical, cross-functional role at the intersection of M&A execution, enterprise go-to-market, and operational excellence. You will lead the critical phase from diligence through integration planning and post-close follow-through, define repeatable integration playbooks, and partner directly with senior stakeholders to ensure each transaction delivers intended value. The ideal candidate brings structured, hands-on integration experience, with particular expertise in enterprise / B2B transactions and a passion for AI, including building an AI-native corp dev platform. This role is based in our San Francisco HQ. 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 integration planning and strategic execution for acquisitions from diligence through post-close follow-through, with clear owners, milestones, risks, and decision points. Translate deal rationale into practical integration goals and plans across product, engineering, sales, partnerships, customer success, people, finance, legal, security, systems, and communications. Partner with deal leads during evaluation and diligence to assess integration considerations, including tech stack, talent assessment, GTM alignment, transaction structure, operational readiness, and execution risk. Advise sponsors on how best to bring onboard acquisitions

About the Team Our London-based team builds the backend systems that help ChatGPT scale reliably. We work on infrastructure close to the product, partnering with engineering teams to improve the performance, resilience, and operability of critical user-facing systems. Our work combines backend software engineering with distributed systems and production reliability. We build shared capabilities, improve high-traffic workflows, and make it easier to introduce new product functionality without compromising performance or availability. About the Role This role is for software engineers who want to build and evolve backend systems operating at significant scale. You’ll write production code, design shared infrastructure, and solve technical challenges involving performance, distributed systems, and system reliability. You’ll also own how those systems behave in production: how changes are rolled out, how issues are detected and diagnosed, and how recurring operational problems can be addressed through better software and system design. This is a strong fit for backend engineers who enjoy complex systems problems and want a direct connection between the infrastructure they build and the experience of ChatGPT users. In this role, you will: Design, build, and maintain backend systems supporting high-traffic ChatGPT experiences. Develop shared services, APIs, and infrastructure that help product teams build and launch new capabilities safely. Improve the performance, scalability, and efficiency of production systems as usage and product complexity grow. Build and improve systems for asynchronous processing and other large-scale backend workloads. Lead architectural improvements and infrastructure migrations while maintaining correctness, compatibility, and safe rollout and rollback. Strengthen monitoring, alerting, and diagnostics to detect problems early and reduce customer impact. Participate in on-call, incident response, and root-cause analysis, and turn operational lea

About the Team The Interpretability team studies internal representations of deep learning models. We are interested in using representations to understand model behavior, and in engineering models to have more understandable representations. We are particularly interested in applying our understanding to ensure the safety of powerful AI systems. Our working style is collaborative and curiosity-driven. About the Role OpenAI is seeking a researcher passionate about understanding deep networks, with a strong background in engineering, quantitative reasoning, and the research process. You will develop and carry out a research plan in mechanistic interpretability, in close collaboration with a highly motivated team. You will play a critical role in helping OpenAI ensure future models remain safe even as they grow in capability. This will make a significant impact on our goal of building and deploying safe AGI. In this role, you will: Develop and publish research on techniques for understanding representations of deep networks. Engineer infrastructure for studying model internals at scale. Collaborate across teams to work on projects that OpenAI is uniquely suited to pursue. Guide research directions toward demonstrable usefulness and/or long-term scalability. You might thrive in this role if you: Are excited about OpenAI’s mission of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s charter . Show enthusiasm for long-term AI safety, and have thought deeply about technical paths to safe AGI. Bring experience in the field of AI safety, mechanistic interpretability, or spiritually related disciplines. Hold a Ph.D. or have research experience in computer science, machine learning, or a related field. Thrive in environments involving large-scale AI systems, and are excited to make use of OpenAI’s unique resources in this area. Possess 2+ years of research engineering experience and proficiency in Python or similar languages. Are deeply curious. About OpenA

About the Team Our infrastructure team helps deliver OpenAI’s most capable models and products to the world by scaling infrastructure and turning demand into useful FLOPS. We collaborate across research, engineering, design, and business to turn cutting-edge AI advancements into impactful, real-world applications. Our team ensures the right compute is available—at the right time and place—to support some of the world’s most demanding workloads. We empower all of OpenAI’s products and research by scaling the infrastructure behind them. Our work makes it possible to launch new models and products reliably and at scale. About the Role As a Data Scientist on the Infra team, you will play a key role in shaping how we scale the infrastructure that powers OpenAI’s products and research. This is critical as we operate one of the largest and most advanced compute fleets in the world, supporting millions of users and businesses globally. We focus on aligning infrastructure measurement, planning, scaling, allocation, and efficiency to drive measurable impact across the company. You should expect to guide the definition of foundational datasets for infrastructure resources, develop metrics that inform key decisions, build forecasting and optimization models, and establish source of truth dashboards and analyses that enable teams to understand and improve infra usage. Most importantly, you should expect to be a core partner to engineering, research, and product teams in shaping the infrastructure that powers everything OpenAI builds. 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: Build and maintain foundational datasets and metrics that reflect infrastructure usage, efficiency, and scaling. Develop forecasting and optimization models to support infra planning and resource allocation. Partner with engineering, research, and product teams to shape infrast

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We’re looking for dedicated, experienced, and deeply curious individuals to help solve some of the most complex challenges faced by our customers while building the future of post-AGI support alongside us. In this role, you’ll work directly with customers through support tickets and live calls, troubleshooting high-impact issues and resolving novel, often ambiguous technical problems in one of the fastest-moving environments in technology. As AI adoption rapidly accelerates, the work you do will directly support mission-critical systems being built on OpenAI’s platform, serving as a critical line of defense for customers operating at massive scale. Beyond resolving technical issues, you’ll help define what world-class support looks like in an AGI-driven future. You’ll partner closely with Engineering, Product, and Operations to improve systems, reduce bugs, and elevate the customer experience, while leveraging automation, agents, and our own AI technology to transform how support operates at scale. You’ll be responsible for: Working directly with customers to troubleshoot and resolve their most complex technical issues, including API failures, integration challenges, authentication errors, and production incidents. Providing end-to-end ownership through debugging logs, analyzing system behavior, reproducing issues, and