Production Associate in United States

MongoDB is hiring a Staff Product Marketing Manager to build and own our go-to-market narrative for the Public Sector vertical, with a focus on Federal Government and the broader public sector market. This is a foundational hire for MongoDB’s Industry Verticals product marketing function: you will define how MongoDB’s unified data platform, spanning cloud, on-premises, and hybrid database deployments with integrated, production-ready AI capabilities, shows up for government buyers. You’ll turn a major compliance milestone into a durable competitive differentiator: developing the positioning, messaging, and sales-ready content that helps government agencies, systems integrators, and cloud/public-sector resellers understand why MongoDB is the right data platform for mission-critical, regulated workloads. You do not need prior government or public-sector work experience to succeed in this role — you need to be an excellent product marketer who can get fluent in a new domain quickly and partner closely with the compliance, product, and sales experts who already are. This role can be based in one of our MongoDB hub offices in the U.S. or remotely in the U.S. What you’ll do Own positioning and messaging for MongoDB’s Public Sector go-to-market, leading the federal GTM and launch related activities Translate MongoDB’s data platform capabilities — document database, search, vector search, stream processing, and integrated AI — into mission-relevant outcomes and value propositions for government buyers and the systems integrators who serve them Partner with Compliance, Security, Industry Solutions and Product teams to accurately represent related certification requirements in external-facing content, staying current as MongoDB pursues additional authorizations (e.g., DoD Impact Levels) Build the public sector sales enablement toolkit: battlecards, pitch decks, discovery guides, ROI/value models, and competitive intelligence tailored to federal buying processes and procuremen

As Engineering Manager for Threat Detection, you will lead a high-performing team that powers Datadog's detection program. Threat Detection is the organization responsible for keeping Datadog ahead of an evolving threat environment: closing coverage gaps faster, raising the bar on signal quality, and shipping detections that hold up under the scale and complexity of cloud-native infrastructure. Your team will combine direct detection expertise, platform engineering, and applied AI to ship detections at a pace and scale traditional rule-writing alone cannot match. Examples of what your team will work on include detection-authoring agents, the detection platform that powers every rule in production, coverage analysis, alert triage and response automation, and the evaluation infrastructure that holds these systems to a high bar of fidelity. Detection authorship is a shared responsibility across the organization, and your team will contribute both by building the systems that scale our authoring capacity and by writing detections directly when their domain expertise is the right tool. You will partner closely with our Security Incident & Response Team (SIRT), Cyber Threat Intelligence (CTI), AI Engineering teams, and Datadog's broader Security organization. This is a high-impact leadership role: you will grow a team of security and software engineers responsible for building and executing our detection and AI strategy. 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: Lead the strategy, roadmap, and execution of Datadog Security's shift to AI-accelerated detection and response. Drive development of high-fidelity detections as a shared responsibility across the organization, ensuring your team's systems and direct contributions raise the bar on coverage and

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

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Stripe Capital provides access to fast, flexible financing to small-and-medium businesses on Stripe to accelerate their growth, and we lent over $1B in 2024. Businesses use the funds for marketing, team growth, geographic expansion, working capital, new equipment purchases, and much more. Machine learning is core to Stripe Capital’s business—we use information about businesses from their activity within and outside of Stripe and our models to automatically underwrite uniquely tailored financing offers to their needs, which banks are often unable to do. We are doing so through models with an established performance history, data infrastructure that is Stripe scale, and a strong feedback loop that includes explainability, anomaly detection and a risk portfolio management layer. We're an end-to-end team going from ideas to models to shipping in production. What you’ll do As a machine learning engineer for Stripe Capital, you'll be responsible for designing, building, training, evaluating, deploying, and owning ML models in production with the goals of providing financing opportunities to as many users as possible while satisfying financial performance goals. You'll work closely with software engineers, data scientists, product managers, and risk managers to operate Stripe’s ML powered systems, features, and products. You'll also contribute to and influence ML architecture at Stripe and be a part of a larger ML community. Responsibilities Design

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 As an AI Accelerator Systems Software Technical Program manager at OpenAI, you will help bring our chips/system hardware roadmap to life, navigating an array of technical and partnership challenges. We’re looking for people excited to push the frontiers of computing by navigating technical explorations and are passionate about building. 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: Manage the end-to-end software development from design to implementation for our AI acceleration systems, working across technical, cross-functional and external stakeholders Lead planning and scheduling of AI system software designs with our strategic partners and vendors Coordinate and lead internal resources and communication for efficient interaction with partners and vendors. You might thrive in this role if you: Have experience as a software technical program manager for data center system products (server, GPU, TPU, networking, storage and so on) taking products from concept to volume in a data center environment ensuring the systems scale with high quality Know end-to-end software development program management techniques from concept, design, production, deployment into the data center Want to help design some of the world’s largest supercomputing systems, working at the edge of complex hardware challenges Enjoy working with and enabling world-clas

About the Team OpenAI for Financial Services is part of OpenAI's Verticals organization, which focuses on accelerating the economy and knowledge work. We build AI products for financial institutions and the professionals who power them, from investment bankers and research analysts to investors and other financial services teams. We combine OpenAI's models, financial data, and enterprise knowledge to help professionals research companies, analyze markets, and produce high-quality work in the tools they use every day. We're a small, entrepreneurial team working closely with customers and partners across research, product, design, engineering, and go-to-market to bring new capabilities from idea to production. About the Role We're looking for full-stack engineers to build new, AI-native products on top of ChatGPT Work and Codex. This is zero-to-one work: you'll help define how financial professionals research, analyze, and make decisions alongside AI. You'll own the experience across the stack, work directly with customers to understand their workflows, and collaborate across OpenAI to turn new model capabilities into products that professionals can trust. Your work will shape how some of the world's largest financial institutions adopt AI and how financial knowledge work gets done. In this role, you will: Build a new financial services app within ChatGPT Work and Codex, creating intuitive AI-native experiences for company research, financial analysis, document review, and professional work products. Develop new product experiences around enterprise memory that learn from an organization's knowledge, workflows, and context, and adapt to how its teams work. Develop the APIs, services, and integrations required to connect user experiences with financial data providers, enterprise systems, and OpenAI's models. Work closely with product and design to turn ambiguous customer problems into polished, useful, and reliable products. Work directly with financial institutions to

About the Team OpenAI for Financial Services is part of OpenAI's Verticals organization, which focuses on accelerating the economy and knowledge work. We build AI products for financial institutions and the professionals who power them, from investment bankers and research analysts to investors and other financial services teams. We combine OpenAI's models, financial data, and enterprise knowledge to help professionals research companies, analyze markets, and produce high-quality work in the tools they use every day. We're a small, entrepreneurial team working closely with customers and partners across research, product, design, engineering, and go-to-market to bring new capabilities from idea to production. About the Role We're looking for backend engineers to build the systems that make advanced AI useful, reliable, and trustworthy in financial services. You'll build the data systems, agentic workflows, and enterprise integrations behind our products. You'll also help bring them into production at some of the world's largest financial institutions. This is a product-minded engineering role with significant ownership and zero-to-one building. You'll shape new products from the ground up, work directly with customers to understand their workflows, and collaborate across OpenAI to turn new model capabilities into products that professionals can trust with high-stakes work. In this role, you will: Design and build backend systems that power AI-native financial workflows across ChatGPT Work and Codex. Build infrastructure to ingest, index, retrieve, and serve financial data, company filings, market information, and firm-specific knowledge at scale. Develop integrations with financial data providers, enterprise knowledge systems, and customer environments, including the authentication, authorization, and entitlements required to use them securely. Build the systems that let models and agents use the right tools and data, preserve source provenance, and produce accurate,

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’re looking for a software engineer to help build the design methodology, software abstractions, and infrastructure that enable a small silicon team to develop complex chips rapidly and with high confidence. You will turn evolving architecture and design needs into reusable tools and workflows that improve iteration speed, quality, and then apply those tools to help construct world-class silicon. You’ll work closely across architecture, design, verification, performance modeling, and systems software. This role is well suited for an engineer who enjoys building high quality software and is motivated by the challenge of improving velocity and quality of the silicon development process. In this role, you will: Develop and scale design methodologies for rapid first-party chip development and apply them to construct complex custom chips Create abstractions that allow hardware structures, configurations, experiments, and results to be represented consistently across tools. Automate high-value engineering workflows and improve their reproducibility, observability, testability, and ease of use. Partner with architects, RTL designers, verification engineers, compiler engineers, and systems software engineers to gather requirements and then implement solutions. Use methodology and tooling to identify design risks early, accelerate iteration, and improve confidence in performance and implementation tradeoffs. Contribute across multiple aspects of software and hardware

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 OpenAI’s GTM Partnerships team builds a strategic, global partner ecosystem that accelerates customer success, enables enterprise AI adoption, and drives durable growth in support of OpenAI’s mission. Cloud partners are central to how customers discover, purchase, deploy, and scale OpenAI solutions. We work across cloud providers and their field, product, marketplace, technical, and partner organizations to reduce friction for customers and create repeatable paths from initial interest to production impact. The team collaborates closely with Sales, Technical Success, Product, Engineering, Finance, Legal, Security, Marketing, Operations, and Customer Success to turn strategic cloud relationships into measurable customer and commercial outcomes. About the Role We are hiring a Partner Director, GTM Cloud Partnerships to shape and execute OpenAI’s go-to-market strategy with strategic cloud partners. You will own senior relationships across a portfolio of cloud providers and develop joint business plans that expand customer access to OpenAI’s products, generate partner-sourced opportunities, and accelerate enterprise adoption. You will translate company-level partnerships into practical field motions spanning account planning, co-selling, cloud marketplaces, customer procurement, technical enablement, solution development, and executive engagement. This is a highly strategic and hands-on role. Success requires executive presence, strong commercial judgment, cloud ecosystem expertise, and the operating discipline to coordinate complex initiatives across multiple partners, regions, and internal teams. The ideal candidate can move fluidly between long-term strategy and the detailed execution required to deliver measurable results. This role is based in San Francisco. We use a hybrid work model of three days in the office per week. In this role, you will: Own the strategic and commercial relationships with a top global cloud partner, establishing strong alignm

About the Team GTM Growth Engineering builds AI-native products that help OpenAI's go-to-market and B2B marketing organizations scale with greater speed, intelligence, and operational effectiveness. We apply OpenAI models to real business workflows and build the systems that make those applications useful and dependable: customer context, agent behavior, feedback, evaluation, experimentation, and appropriate human oversight. Our work brings together software engineering, applied AI, product, data, and GTM operations. We measure success through the quality of customer engagement, pipeline, conversion, and the effectiveness of our sales and marketing teams. About the Role We're looking for an Applied AI Engineer to build production systems that help AI-powered go-to-market workflows improve over time. You will connect agent behavior, customer and operator feedback, evaluation, experimentation, and business outcomes to make these systems more effective, reliable, and responsive to evolving customer needs. This is a deeply technical, cross-functional role with end-to-end ownership of the agent improvement loop: understand production behavior, identify failure modes, improve how the system decides or acts, and validate the resulting impact. You will partner with Engineering, Product, Data Science, Sales, and B2B Marketing to turn real-world signals into safer, more effective agent behavior and measurable improvements in customer engagement, conversion, qualified pipeline, and team productivity. In this role, you will: Own the production improvement loop across agent behavior, customer and operator feedback, evaluation, experimentation, and verified business outcomes. Instrument agent workflows so model interactions, tool use, decisions, failures, human edits, and downstream outcomes can be understood in context. Define meaningful quality standards, representative evaluation datasets, regression coverage, and production monitoring for real GTM workflows. Investigate why a

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role You’ll own the hands-on and automation work that brings WAN, fiber, carrier, and cloud-interconnect circuits into service. Partner with network engineers, fiber providers, cloud service providers, colocation teams, and data-center technicians to move each connection from ordered and patched to verified, stable, and ready for handoff. You’ll own Layer 1 troubleshooting and circuit bring-up while building workflows that translate reliable system or model output into precise, approved technician actions, capture field feedback, and drive each connection to a green-port handoff. The right person combines strong physical-networking judgment with practical automation skills: patch-panel and port mappings, optics and light levels, provider coordination, structured operational data, API or scripting workflows, and human-in-the-loop LLM tooling. Responsibilities Own Layer 1 activation and restoration for carrier circuits, dark fiber, wavelengths, Ethernet handoffs, and dedicated cloud interconnects across data centers and points of presence. Reconcile complete A-side/Z-side as-builts: circuit IDs, LOAs/CFAs, carrier demarcations, MMR/ODF/MDF and patch-panel positions, fiber pairs, cross-connects, optics, and device ports. Investigate no-light, low-light, wrong-port, link-flap, and error-rate issues across providers and CSPs; isolate continuity, dirty connectors, polarity, incorrect patching

About the Team API Multimodal builds the developer-facing products and infrastructure that bring OpenAI’s image, audio, and real-time model capabilities into the world. We are responsible for high-scale APIs for image generation, speech transcription, speech generation, and low-latency voice interactions. We partner closely with Research and Inference to bring frontier model capabilities to developers and use customer feedback to improve our models. About the Role As a software engineer on API Multimodal, you will build and operate the products and distributed systems behind OpenAI’s image, audio, and real-time APIs. You will work across model integration, API design, and production infrastructure to turn new research capabilities into reliable developer experiences. This hands-on role combines backend and systems depth with product judgment: you will own projects end to end, partner with Research, Inference, and Safety, and help make multimodal AI useful at scale. Model training experience is not required. In this role, you will: Design, build, and ship developer-facing APIs and backend services that serve frontier models. Architect low-latency streaming, request, session, and model integration systems that make complex multimodal interactions reliable and intuitive at scale. Work directly with Research to bring new model capabilities into production, shape the systems around them, and incorporate feedback from real-world developers and customers. Own the availability, latency, scalability, and cost efficiency of the services you build. Own projects from technical design and implementation through launch and ongoing iteration, while raising the team’s engineering standards. Your background might look something like: 7+ years of professional experience, excluding internships, in backend, infrastructure, platform, or product engineering roles. A track record of designing, building, and operating production backend services, developer-facing APIs, or distributed syste

About the Team The Enablement Lead (EL) team enables organizations to turn OpenAI products into real, sustained impact through world-class enablement and training execution. Our mission is to help customers successfully adopt and operationalize AI across their organizations. We partner with enterprises to translate the potential of OpenAI’s technology into durable capability—through structured training, technical enablement, and scalable deployment programs. By helping customers move from experimentation to production, the EL team accelerates time-to-value, deepens product adoption, and helps make OpenAI indispensable to how organizations work. About the Role The Enablement Lead, Builder role is a specialist post-sales technical enablement role focused on delivering high-impact enablement and adoption services across OpenAI’s product suite. You will design and deliver technical learning experiences covering OpenAI APIs, Codex, agents, evaluations, and related platform capabilities. You will work with engineers, AI and platform teams, administrators, security stakeholders, product leaders, and executive sponsors. This role blends deep technical fluency, instructional design, and customer advisory. You will lead live trainings, workshops, and adoption interventions for audiences ranging from hands-on builders to executive leaders, helping customers understand not just what OpenAI’s products can do, but how to use them effectively in real-world contexts. Success in this role means accelerating customer confidence, increasing product adoption, helping customers progress toward production use, and turning lessons from individual engagements into resources and practices that benefit many customers. 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: Own the technical enablement of OpenAI products, including OpenAI APIs, Codex, Agents, Evaluations a

About the team The Agent Enablement AI Deployment Engineering (ADE) team works across engineering, product, design, partnerships, and strategic customers to grow an open ecosystem of agent-enabled sites and services. We help partners adopt the OpenAI tech stack related to identity, permissioning, agent-auth primitives so users can safely connect ChatGPT and Codex to the tools, services, and workflows they already use. Our team also works with external partners on defining the standards for agent access, marketplace offerings as well as other agent enablement initiatives to ensure users of ChatGPT and Codex go from intent to task completion seamlessly. About the role We are looking for an AI Deployment Engineer to help strategic partners design, build, validate, launch, and operate agent enablement integrations across web applications, connectors, APIs, CLIs, MCP servers, and developer tools. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated technical engagements, and turn ambiguous identity and agent-workflow requirements into secure, production-ready integrations. You will work across partner product and engineering teams and OpenAI’s product, engineering, design, partnerships, legal, policy, security, support, and go-to-market teams. You will identify high-value user journeys, choose the right integration path, prototype and review architectures, write code, run evaluations and dogfood, trace failures end to end, guide launch and rollout, and support post-launch iteration. The best person for this role moves fluidly between full-stack code, OAuth/OIDC and identity systems, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product-minded engineer who wants to stay close to users and partners while going deep on authentication, permissions, reliability, safety, and developer experience. The principle objective is to