Large Enterprise Account Executive Auth0 in United States

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. We are the Data Foundation & AI team within Plaid’s Data organization. Our mission is to build the shared ML and AI infrastructure that powers intelligent capabilities across Plaid’s product suite. We develop the foundational systems, models, and data assets that transform Plaid’s unique financial network data into scalable, general-purpose representations that teams across the company can leverage. Our work spans the full ML lifecycle — from large-scale data curation and model pretraining to production serving, evaluation, and monitoring. As part of the team, you’ll work at the intersection of machine learning infrastructure, applied AI, and distributed systems, helping establish the core AI platform that enables innovation across Plaid. As a Staff Machine Learning Engineer, you will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment, feature management,

We are a team of engineers that translate our real-world experience to help our user communities solve problems. With a focus on service management, helping teams respond to incidents, run on-call, and automate their operations, you will work with practitioners and leaders across the industry and broaden your impact to the SRE, Engineer, DevOps, and Operations community at large. This is a unique opportunity to use both your engineering and creative storytelling skills to shape the landscape in cloud observability, incident response and service management. What You'll Do: Act as a subject matter expert for service management (incident response, on-call, IDP, Work Management, Workflow Automation, Agent Builder, and operational automation) for Datadog's advocacy and engineering teams Create content in one or more mediums to build Datadog's reputation as a leader in DevOps, Monitoring, Observability and Security e.g. building demos, public speaking, blogging, documentation, webinars, open source, research reports and more Partner with product engineering teams to build compelling demos, and coach internal engineering teams on effective communication and presentation Interface with open source communities to drive key messaging in the market and develop new integrations for Datadog Contribute to the product through feedback (bugs or product enhancements suggestions), documentation, or code Who You Are: Approximately 5+ years of experience as a Platform Engineer, Site Reliability Engineer, DevOps Engineer or Software Developer with hands-on experience as an on-call/incident responder and running production systems in complex IT environments You have a strong understanding of core service-management practices (incident response, on-call, post incident reviews, and SLOs), using tools like Datadog, PagerDuty, Opsgenie, incident.io, Rootly, Jira Cloud Platform, Cortex, or similar and know how to navigate operational challenges of different s

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join Our Team… GoDaddy's Global Storage Engineering team operates one of the largest Ceph environments in the industry, powering the object, block, and file storage platforms that underpin hosting, applications, internal infrastructure, and next-generation AI/HPC workloads. If you're passionate about distributed systems, large-scale storage architecture, and solving complex reliability challenges, you'll work on infrastructure that few engineers ever experience. At GoDaddy, Ceph isn't a side project — it's a critical platform. Our environment spans 80+ production clusters, 20,000+ OSDs, and approximately 300 PB of raw storage capacity, supporting tens of billions of objects across multiple continents. The scale demands deep technical expertise in storage architecture, automation, observability, and performance engineering. As a Senior Site Reliability Engineer, you'll be a key technical owner of the platform, responsible for maintaining reliability, driving operational excellence, and influencing the future evolution of our storage ecosystem. You'll tackle challenging production problems, develop automation that operates at massive scale, contribute to architectural decisions, and collaborate with some of the industry's most experienced Ceph engineers. This is an opportunity to have direct impact on a storage platform that serves millions of customers worldwide. What You'll Get to Do… Own the reliability, performance, scalability, and capacity of large-scale production Ceph environments supporting object, block, and file storage wor

About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Opportunity: Datadog’s Senior Staff Engineers are technical leaders operating at the forefront of large-scale systems design, building the infrastructure that will support our next five years of growth and beyond. They do this in three major ways: As individual contributors, they bring world-class technical depth to build industry-leading systems in areas such as observability data platforms, distributed query engines, and real-time event streaming at global scale. As technical leaders, they apply broad architectural perspective and deep systems thinking to align design decisions across teams and domains. They work across complex, multi-team problem spaces to define long-term technical direction, drive large-scale initiatives forward, and ensure consistent execution. As engineering stewards, they play a key role in evolving our systems and engineering culture. They actively participate in Datadog’s senior technical community, bringing external insights and internal experience to elevate engineering standards and mentor the next generation of technical leaders. Examples of projects a Senior Staff Engineer may lead include designing and launching a new distributed data storage engine capable of handling hundreds of millions of records per second, building the real-time infrastructure behind a new observability product, or re-architecting a core service to support exponential growth in throughput and complexity. What You’ll Do: Be the technical owner of multiple critical systems or architecture areas, often spanning several t

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

We are a team of engineers that translate our real-world experience to help our user communities solve problems. With a focus on AI-accelerated workflows and next-generation developer ecosystems, you will have the opportunity to meet fast-moving teams where they are, helping them lay strong engineering foundations and broadening your impact to the developer community at large. This is a unique opportunity to use both your engineering depth and authentic storytelling skills to shape how the next wave of builders approach software health, scalability, and observability. What You’ll Do: Help developers hone their craft in an AI-accelerated world by exploring how AI coding assistants and rapid-prototyping tools change software workflows, and guiding teams on how to balance rapid prototyping with established engineering practices around performance, code health, and system reliability. Build in public by creating authentic, peer-to-peer technical content, sharing your engineering insights directly where modern developers collaborate in person and online. Drive a constructive, bidirectional feedback loop between fast-moving developer communities and our internal teams, translating real-world developer experiences into actionable product insights to shape our roadmap while advocating for user needs from the inside. Design and ship high-quality open-source boilerplate templates, quickstarts, and tools that make integrating observability seamless across AI native workflows, next-gen platforms (Vercel, Supabase, etc.), and cloud providers (AWS, GCP, Azure). Who You Are: A builder with approximately 10+ years of software engineering experience, ideally having shipped applications from scratch or worked within an early-stage startup environment where you've worn multiple hats. An AI-fluent developer who natively leverages AI coding assistants and rapid-prototyping tools as a core part of your regular, day-to-day development workflow. Multi-stack familiar, comfortable writing an

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