Large Enterprise Account Executive in United States

Datadog is seeking curious, driven interns to join our Product Management team and help build products that improve how engineers monitor and understand their systems. As a Product Management Intern, you'll support the product development lifecycle by partnering closely with Engineering, Design, and Product Marketing to bring new ideas and features to life. You'll gain hands-on experience working on products that serve highly technical customers while contributing to meaningful business and user outcomes. Interns are embedded directly within product teams, working on meaningful initiatives alongside full-time Product Managers and contributing to actual product decisions. Our platform processes over 100 trillion events per day across 30,000+ customers in a multi-cloud environment -- giving you direct exposure to large-scale, real-time systems built by engineers, for engineers. It's an environment where you'll develop product thinking, technical communication, and cross-functional collaboration skills by doing the work, not just observing it. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Conduct customer discovery conversations and gather feedback to better understand user needs Drive product initiatives from concept through launch alongside Engineering, Design, and Product Marketing teams Translate customer and business needs into clear product requirements and engineering priorities Analyze customer feedback, product data, and market insights to help inform product decisions Prepare and deliver technical product demonstrations and communication materials Develop technical understanding of Datadog’s observability platform and cloud infrastructure products Who You Are: Targeting a 2028 full-time graduation or start date Pursuing a degree in

Datadog is seeking a Director of Product Management for Platforms to lead the internal platforms that power our global engineering organization. This is both a customer and internal platform leadership role, focused on enabling Datadog customers to maximize value with Datadog but also to enable other Datadog products to build, scale, and operate products efficiently and reliably. In this role, you will bring a combination of technical expertise, product management experience, and a deep understanding of platform and shared capabilities to help Datadog grow its leadership position. You will lead a team of product managers and collaborate with senior leadership in product, engineering and design. Your scope includes driving product features shared across all Datadog but also large-scale Datadog’s platform solutions. What You’ll Do Own the vision and strategy for platform products, ensuring alignment with overall company goals and customer needs. Identify new opportunities for innovation and drive them from concept to execution, ensuring they have a measurable impact on customers and the business. Define product roadmaps and manage the prioritization of features and initiatives to ensure the team's efforts are aligned with business goals. Drive Platform Adoption: Partner with engineering and product teams to ensure widespread adoption of shared platforms and shared features, reducing duplication and accelerating delivery. Improve Operational Efficiency: Improve developer velocity, time-to-production, and operational efficiency across Datadog’s engineering ecosystem. Collaborate with cross-functional teams including engineering, design, data science, marketing, and sales to deliver infrastructure product solutions that meet customer needs and business objectives. Define and Track Success Metrics: Define and track platform success metrics, including adoption of platform capabilities, reduction in internal toil, time-to-production improvements, cost efficienc

MongoDB Atlas is the premier multi-cloud database-as-a-service built and operated by the makers of MongoDB. The Cloud Operations Engineering team at MongoDB is a worldwide team responsible for the consistent operational success of every MongoDB Atlas customer. As a Cloud Operations Engineer, you will help ensure the success of our Atlas customers, whether they are early startups or large multinational companies, cloud-native or just getting started with a digital transformation to the cloud. You are excited about the core mission of MongoDB, and the opportunity to join the team responsible for operating Atlas, the fastest-growing multi-cloud database-as-a-service in the world. You are prepared to be one of the founding members of a 24/7/365 global cloud operations team. Cloud Operations Engineers will be responsible for day-to-day duties such as creating and monitoring systems alert dashboards, reviewing critical event and system logs, accessing customer instances that underpin their production databases and performing server administration duties including performance troubleshooting. Applicants must be critical thinkers who are quick to detect, resolve, or escalate issues that are sometimes broad in scope and difficult to trace. FedRamp engineers are specifically tasked with supporting our government customers in our FedRamp Atlas environment. This includes SLED (State and Local Government and Education), various federal agencies, and other customers that leverage FedRamp. At MongoDB you will grow your career and skills, wear multiple hats, and be part of an operations team that works at the frontier of Cloud services and database systems. This role will be based remotely in Colorado. Responsibilities Successfully coordinate with a global team of Cloud Operations Engineers who are tasked with ensuring our uptime guarantees to our Atlas customer base Help scale the worldwide Cloud Operations Engineering team with the strategic implementation of new processes and to

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: As a key part of the Localization Operations team, you will be responsible for driving the future process, tooling and automation of how Airbnb delivers high-quality, culturally resonant experiences to users around the world at large scale. The Difference You Will Make: Airbnb Localization team is seeking a Technical Program Manager (TPM) to lead high-impact initiatives at the intersection of localization, technology, and global scale. This role calls for a unique blend of deep technical expertise, strategic program leadership, and the ability to deliver innovative, scalable solutions that transform how localization is executed. You’ll partner across engineering, product, and external vendors to ensure our tools, processes, and technologies evolve in step with the fast-changing global tech landscape. A Typical Day: Own and drive complex, cross-functional localization programs from strategy through execution, acting as the single point of accountability for technical localization operations. Serve as a trusted operating partner to Localization Operations and Localization leadership, translating strategic priorities into executable technical roadmaps and surfacing tradeoffs early. Lead the design, innovation, and implementation of scalable solutions leveraging technology including AI and machine translation to improve on the quality, cost and efficiency of localization delivery. Shape the technical direction of Localization at Airbnb through alignment with Localization Leadership on vision and business goals, leveraging SME expertise across the Localization organizati

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We're looking for an Optical Interconnect System Engineer to design, qualify, and deploy scalable optical connectivity for large-scale AI infrastructure. This role spans fiber-system architecture, optical-mechanical integration, validation, reliability, deployment, and serviceability. You will work with optical, mechanical, electrical, networking, manufacturing, reliability, and data-center teams to translate system needs into practical interconnect solutions. This is a hands-on role for someone who can connect design decisions with installation, qualification, troubleshooting, and long-term operational performance. In this role, you will: Define optical interconnect architectures and requirements across hardware platforms and rack-level systems. Design high-density fiber systems for performance, density, reliability, installation, and serviceability. Lead optical-mechanical integration and cross-functional design reviews. Develop test and qualification plans for optical components, modules, switching platforms, and integrated systems. Own optical loss budgets, routing guidelines, handling requirements, and serviceability criteria. Support system bring-up, deployment, troubleshooting, failure analysis, and reliability improvement. Create reusable design guidelines, interface requirements, and qualification methods. You might thrive in this role if you have: Core experience Experience desi

About the Team The Capital Markets team develops the financing strategy, solutions, and partnerships needed to support our expanding global AI infrastructure platform and long-term investment plans. About the Role We’re looking for a senior structured finance leader to create immediate execution leverage for a growing capital markets function. In this role, you’ll take broad financing objectives, such as raising a large pool of capital from a defined set of counterparties, and independently turn them into well-run transaction processes. You’ll lead complex financings from strategy through close, manage counterparties and advisors, and bring sound judgment to capital structure, risk allocation, process design, and execution. This is a hands-on role for someone who is still close to the details, not a purely senior relationship manager. Your work will allow the team lead to spend less time in day-to-day execution and more time building the broader capital markets organization. In this role, you will: Lead large, complex financing processes from initial structuring through diligence, negotiation, documentation, and closing. Translate broad capital-raising objectives into executable financing plans, timelines, work streams, and counterparty strategies. Manage lenders, investors, advisors, counsel, and internal stakeholders across high-stakes transactions. Provide oversight on financial structuring, modeling, diligence, risk allocation, and transaction documentation. Make clear recommendations on financing strategy, counterparty selection, process design, and tradeoffs. Operate effectively in a small, high-impact team without relying on a large analyst or associate bench. Help build repeatable internal processes for a financing function that is still scaling. Coach and develop more junior transaction professionals. You might thrive in this role if you have: 8-15 years of experience executing structured finance, project finance, infrastructure finance, digital infrastruct

About the Team Our economics team is continuously working to improve our understanding of an AI-driven economy. About the Role We are seeking a highly technical Economist to join the OpenAI Economic Research team studying the real-world economic impacts of AI. This role is designed for economists with up to 5 years of professional experience post-Ph.D. who are interested in using novel, large-scale datasets to study how AI is reshaping economic systems. We are looking for candidates with deep expertise in at least one core domain relevant to AI’s economic impact, and an interest in contributing to a broader research agenda spanning labor markets, firm behavior, market dynamics, and macroeconomic change. This is an individual contributor role where the candidate will organize and execute on their own data-oriented projects. You will work at the intersection of economic research, data science, and public policy to produce rigorous empirical work that informs decision-makers across the public, industry, and government. Research Areas of Interest We are particularly interested in candidates with demonstrated expertise in one or more of the following areas: Economic Measurement of AI Impact (e.g., adoption trajectories, labor market transitions, productivity growth, and forecasting/scenario modeling for AI-driven economic change) Macroeconomic Implications of AI (e.g., productivity, technology diffusion, economic growth) AI and the Labor Market (e.g., employment, wages, job search, task-level impacts, skill acquisition) Applicants are not expected to have experience across all domains. We aim to build a team with complementary strengths across these areas. In this role, you will: Design and execute empirical research using large-scale observational or experimental data. Apply causal inference and/or structural modeling techniques to study AI-driven economic change. Collaborate with cross-functional teams to translate research questions into testable frameworks and applic

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Through strategic partnerships and self-built campuses, we are scaling one of the world's fastest-growing AI infrastructure platforms. The Supply Chain organization ensures critical infrastructure components—from compute systems and networking equipment to integrated rack solutions—are sourced, manufactured, qualified, and delivered with the speed and reliability required to support frontier AI development. We partner closely with Hardware Engineering, Manufacturing Quality Engineering, Infrastructure Delivery, Hardware Operations, Finance, and suppliers worldwide to build a resilient, scalable supply chain capable of supporting rapid infrastructure expansion. As Industrial Compute continues to grow, Supply Chain serves as the operational bridge between engineering innovation and large-scale infrastructure deployment. About the Role We are seeking a Supply Chain Manager to lead strategic execution across sourcing, supplier operations, manufacturing quality, and infrastructure delivery for OpenAI's AI infrastructure portfolio. This role will oversee a multidisciplinary team responsible for strategic sourcing, manufacturing quality engineering, and technical program management while partnering closely with engineering, finance, hardware operations, and deployment teams. You will drive supplier strategy, manufacturing readiness, production planning, quality performance, and operational execution across the full hardware lifecycle. Success requires balancing long-term supplier strategy with day-to-day execution. You'll establish scalable operating mechanisms, strengthen supplier partnerships, manage complex cross-functional programs, and ensure OpenAI can rapidly deploy AI infrastructure without compromising quality, cost, or reliability. This is a people leadership role responsible for developing a high-performing organization while driving operati

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. The Power & Land team owns the energy strategy required to secure reliable, scalable, and economically resilient power for OpenAI’s global data center portfolio. About the Role The Power Trading Lead will own commodity hedging strategy and execution across OpenAI’s data center power portfolio. This role will translate large, dynamic electricity and fuel exposures into practical hedging, procurement, and risk-management strategies that protect infrastructure economics while preserving flexibility for growth. This is an individual contributor lead role and does not have direct reports initially. The role will work across power markets, utility tariffs, retail and wholesale supply structures, natural gas and power hedges, renewable and clean firm products, and portfolio risk analytics to support long-term compute growth. Key Responsibilities Develop and maintain OpenAI’s commodity hedging strategy across electricity, natural gas, and related energy exposures for data center operations and growth. Quantify portfolio exposure by market, site, load shape, tenor, tariff, and supply structure, and translate that exposure into clear hedging recommendations. Evaluate and execute hedging structures including fixed-price supply, forwards, swaps, options, retail supply products, congestion and basis risk mitigation, and related instruments where appropriate. Partner with utilities, suppliers, traders, banks, consultants, and market counterparties to source competitive products and improve risk-adjusted energy economics. Build decision frameworks for when to hedge, how much to hedge, and which risks to retain across different stages of site development, construction, and operations. Coordinate with finance, treasury, legal, procurement, energy regulatory, sustainability, and site-readiness teams to ensure hedging strategy aligns with broa

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a

By applying to this role, you will be considered for Research Engineer roles across all teams at OpenAI. About the Role As a Research Engineer here, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed. The most outstanding deep learning results are increasingly attained at a massive scale, and these results require engineers who are comfortable working in large distributed systems. We expect engineering to play a key role in most major advances in AI of the future. We expect you to: Have strong programming skills Have experience working in large distributed systems Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms 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 systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment

About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We operate at the front line of real-world safety and risk management, translating user and operational signals into timely decisions, effective interventions, and improvements to our systems. This role sits on a new team within USRO focused on building operational capacity for new, ambiguous, or fast-moving areas of work. The team helps define what needs to be built, creates the operating model to support it, and works with partner teams to make the work scalable and durable over time. As a Strategic Operations Lead, you will focus on large, cross-functional initiatives that require clear thinking, technical fluency, strong execution, and the ability to bring structure to undefined problems. About the Role We are seeking a Strategic Operations Lead to drive new and existing strategic operating builds across User Safety & Risk Operations. This is a senior IC role for someone who can turn broad, undefined priorities into clear operating models, launch plans, requirements, stakeholder alignment, documentation, reporting, and execution rhythms. This role will often support initiatives where OpenAI is developing new products or partnerships and the operating model is still being defined. These programs have a direct user safety and risk nexus because new deployment models can change what signals OpenAI can see, who owns response decisions, and how user-impacting risks are detected, escalated, and resolved. You will clarify what OpenAI owns, what partner teams own, what signals we can reliably monitor, how issues should be escalated, and how the workflow should evolve from launch support into a durable operating model. The right person is highly strategic and deeply practical. They can move from executive-level framing to detailed workflow design, stakeholder management, SOPs, launch readiness, ri

By applying to this role, you will be considered for Research Scientist roles across all teams at OpenAI. About the Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the team you work on, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company. We expect you to: Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms 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 systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for

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 Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training. We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings. Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models. About the Role As a Software Engineer on the Frontier Systems team focused on power management, you will work on critical infrastructure to support cutting-edge research. With large-scale supercomputers consuming substantial amounts of power, managing this efficiently is key to maximizing computational capacity. This role is critical to ensuring that our cutting-edge research supercomputing infrastructure runs smoothly, while maintaining reliability and grid-level power stability. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Develop and implement system-level and software-level solutions to optimize power usage in large-scale supercomputers, ensuring efficient and reliable operations. Build automation to monitor power consumption patterns during training workloads and design algorithms to stabilize these fluctuations, preventing issues with grid reliability. Work with researchers and engineers to design tools for real-time monitoring, detection, and remediation of power-related hardware and system faults. Collaborate cross-functionally to translate complex electrical system requirements into code, while driving continuous improvements in power man