Application And Web Security Specialist in United States

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—allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team: The Revenue Data Engineering Teams designs, builds and runs the data pipelines and helper systems to accurately and in a timely manner quantify our customers’ usage across all Datadog products. This team is at the leading edge of any new product we release. The Revenue Data Processing team builds and operates the data pipelines that does billing, and cost attribution for all Datadog products. We process terabytes of data daily to power revenue-critical systems and are at the center of every new product launch at Datadog. As a Senior Software Engineer, you will own meaningful parts of a large-scale, mission-critical processing platform — driving architectural improvements, building new billing capabilities, and maintaining the high reliability bar our downstream consumers depend on. You Will: Design and build high-throughput data pipelines for billing and cost attribution Drive platform improvements — latency reduction, Spark optimization, sharding, and cross-datacenter reliability Own root-cause investigations on billing accuracy issues in collaboration with Finance and Product teams Contribute to new billing features Work across Python and Scala, with technologies including Spark, Airflow, Trino, and Apache Iceberg Participate in on-call rotation and maintain a high reliability bar for production systems Contribute to engineering standards and help grow the technical culture of the team You Are: You have significant experience building and operating production data pipelines at scale using Spark and Airflow

About the Team The Human Data team turns human feedback into reliable signals for training and evaluation. We design and run end-to-end programs that capture the depth of human intent behind everyday and high-stakes uses of our models. Our remit spans bespoke data campaigns, scalable synthetic data generation, and product-embedded signals. We partner closely across all research teams to translate these signals into training datasets, novel evaluations, and feedback loops that push the frontier of our models and advance their applications. About the Role As a Program Manager (PGM) in the Human Data team you will partner with our research teams, operations and engineering to execute complex programs for collecting high-quality data. You will be a key interface between our external vendors and AI trainers, ensuring human data campaigns are successfully completed. Your work will play a key role in enabling OpenAI to train safe models that will land in the real world This role is based in our San Francisco HQ. In this role, you will: Work in a high velocity environment, where the outcome of your work will have a direct impact on the models that OpenAI deploy in the real world Work closely with external vendors, trainers and internal researchers to collect, review, and deliver high-quality data Gather requirements, write instructions, define success criteria, and calibrate the AI trainers Use internal tooling to assess labeled data and provide feedback to AI trainers Think critically and share recommendations on tooling and process improvements, optimizing for quality, throughput, and AI trainer experience You’ll thrive in this role if: You thrive in dynamic environments. You are comfortable navigating ambiguity, managing shifting priorities, and adapting to fast-paced changes without missing a beat. You’re curious about AI, LLMs, Agents. While not required, an interest or background in these areas will help you connect the dots in our broader mission. You have a can-do a

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for Members of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. You may be a good fit if you have: 5+ years of engineering experience running production infrastructure at a large scale Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters Experience with Kubernetes dev and production coding and support Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving Experienc

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Are you energized by leading the design of high-performance, scalable and reliable machine learning systems? Do you want to set technical direction and help shape the next generation of AI platforms powering advanced NLP applications? We are looking for a Lead Member of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will provide technical leadership across multiple teams, driving the architecture and strategy for deploying optimized NLP models to production in low latency, high throughput, and high availability environments. You will serve as a key point of contact for customers, leading the design of customized deployments to meet their specific needs, and mentoring engineers to raise the technical bar across the team. You may be a good fit if you have: 8+ years of engineering experience running production infrastructure at a large scale, with a track record of technical leadership Demonstrated experience leading the architecture

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: Join a team that builds robust, real-time distributed systems for a cutting-edge database. We care about performance, reliability, scalability, and most of all learning and having fun together. Whether you’re a seasoned coder or just getting started, if you’re passionate about technology and eager to learn, you’ll fit right in. Who we are: We show up to work, ready to collaborate and build technologies that make a difference, with people who genuinely care. We chase improvements such as tail latencies, bytes throughput, cache hit rate, and operational cost efficiency. We believe learning is ongoing and that even the most complex problems can have simple solutions. What You’ll Do: Collaborate with teammates to design and build database features that power AI applications. Learn how to tune performance and support reliability in distributed systems (don’t worry, we’ll guide you). Help Pinecone run smoothly on popular cloud providers. Take ownership of your work and grow your skills every day. Have fun. Who You Are: 5+ years of work experience - programming in Rust, Go, C++, or a comparable language. You’re genuinely curious about distributed systems and eager to dive deep into technical challenges. You approach problems with creativity and persistence, and you’re comfortable asking thoughtful questions or seeking feedback. You’re excited to learn, value constructive feedback, and appreciate mentorship. Bonus Points: You have hands-on experience with cloud platforms (AWS, GCP, Azure) or have demonstrated an ability to pick u

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. You'll build the agentic AI system that powers creation for millions of Roblox creators. The Assistant team is converging Studio Assistant (desktop) and Build (mobile) into a single cloud-native architecture — one harness, one tool set, one eval framework. You'll work across the full stack: cloud orchestration, LLM integration and model routing, tool/skill execution, and the creator-facing client. The system orchestrates multi-step creation workflows end-to-end: planning, code generation, asset creation, and automated testing. You Will: Help and understand the needs of the community that uses our software, from beginning artists to professional scripters and designers. Take ownership and responsibility for designing, building, testing, and deploying services within the Roblox ecosystem. Work on a variety of unique technical challenges within complex systems. Be a technical bar-raiser for high code quality, architectural designs, and long-term planning. Develop fellow engineers on the team. You Have: 5+ years of experience shipping high-complexity software and supporting mission-critical applications at scale. Experience architecting, designing, and leading implementation across a wide range

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. 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: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r

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

MongoDB is transforming the $138B+ data management software market by empowering developers to build the next generation of applications. As the leading modern data platform—and the first database company to IPO in over 20 years—we're at the forefront of innovation. We are seeking a driven, experienced commercial attorney to lead and scale our U.S. Public Sector and government contracting business. Operating in a fast-paced, high-growth environment, you will serve as the primary legal partner for our public sector sales ecosystem, managing complex transactions and ensuring strict regulatory compliance. This role can be based out of our US offices or remotely in the United States. Core Responsibilities & Requirements End-to-End Deal Execution: Draft, structure, and negotiate high-value public sector and commercial transactions, including SaaS, cloud licensing, professional services, and subcontracting agreements Public Sector Compliance: Provide expert guidance on U.S. and international government procurement laws, including FAR/DFARS frameworks, GSA schedules, and FedRamp requirements, and support ongoing development and refinement of public sector compliance program Strategic Sales Advisory: Advise cross-functional teams throughout the public sector sales lifecycle, from initial RFP evaluations and proposal risk assessments to handling audits or disputes Operational Scalability: Build, refine, and maintain legal playbooks, contract templates, and training modules to streamline negotiations and empower sales teams Regulatory Monitoring: Stay ahead of evolving technology laws, government contracting regulations, and government and defense related export controls to provide proactive, actionable risk mitigation strategies Cross-Functional Collaboration: Work cross-functionally to launch new programs to support growth of commercial and public sector businesses Requirements: 8+ years of US public sector transactions experience, preferably at a law firm a

About the Team API Enterprise Controls is part of the API Infrastructure organization and owns the platform capabilities that help developers, startups, and enterprises adopt the OpenAI API securely and confidently. We build the systems underneath our APIs and developer platform across authentication and identity, service accounts and key management, secure networking, compliance, auditability, observability, and operational controls. Our users are developers and teams running critical applications on OpenAI, and we partner closely with Product, go-to-market, security, and infrastructure teams to turn their most important needs into reliable, intuitive platform capabilities. About the Role We are looking for an exceptional backend software engineer to help define and ship the enterprise capabilities our API Platform needs to scale.; this is a product-engineering role grounded in deep backend systems. You will work across databases, streaming systems, request routing, authentication, and developer-facing APIs while bringing strong product judgment, developer empathy, and attention to the small details that make a platform easier to understand, trust, and operate. You will lead large cross-functional initiatives, work closely with Product and go-to-market teams, engage directly with sophisticated users, and carry ambiguous needs from discovery through design, launch, and iteration. In this role, you will: Own backend product capabilities end to end across authentication and identity, service accounts and key controls, secure networking, compliance, observability, and operational workflows. Partner with Product, go-to-market, security, infrastructure teams, and sophisticated customers to identify needs, shape the roadmap, and lead large cross-functional projects from design through launch. Design developer-facing APIs, system behavior, configuration, error handling, safe defaults, auditing, and notifications with exceptional care for the details that define a great dev

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. In the Model Experience team, we shape the default character and behavior of ChatGPT: how the model communicates, responds to users, uses its capabilities, and behaves across different contexts and languages. Our goal is to make every interaction with ChatGPT thoughtful, helpful, and trustworthy. We take an opinionated view of what good human–AI interaction should look like, then turn that vision into real model behavior through human data, evaluations, reward models, and post-training. Our work sits at the intersection of research, product, and model design. We partner closely with teams across OpenAI to conduct research and ensure our models are thoughtful, safe, reliable to serve millions of users. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research and the quality of human-AI interaction. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have good judgment about model behavior and can communicate this judgment effec

About the Team OpenAI’s API Platform organization builds the products and infrastructure that help first-party and third-party developers build with OpenAI models. We ship the API primitives, tools, SDKs, documentation, playgrounds, and platform experiences that make OpenAI’s capabilities reliable, understandable, and useful in production. The API Experience team is focused on the end-to-end developer experience for the OpenAI API. We own the surfaces developers touch every day: docs, SDKs, the Playground, examples, onboarding flows, and the systems that help developers go from first request to production deployment quickly and confidently. About the Role We’re looking for full stack and frontend engineers to help define and build the next generation of OpenAI’s developer experience. In this role, you’ll work across frontend product surfaces, backend systems, SDK and documentation pipelines, and API workflows that serve millions of developers and companies. You’ll partner closely with product, design, research, API engineering, and developer-facing teams to make complex AI capabilities simple to understand, easy to test, and safe to launch in real-world applications. This is a highly cross-functional role for someone who cares deeply about craft, developer empathy, reliability, and product velocity. In this role, you will: Build and scale developer-facing products including the OpenAI API Playground, documentation experiences, onboarding flows, examples, and API workflow tools. Own full stack projects end to end, from product definition and UX collaboration through backend implementation, launch, measurement, and iteration. Improve the systems that generate, maintain, and publish SDKs, API references, docs, guides, and developer examples. Partner with API, research, design, and infrastructure teams to bring new model capabilities and API primitives to developers in a clear, usable way. Use developer feedback, product analytics, and direct customer insight to identif

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have a working knowledge of relevant models, and building evaluations for model capability improvement. Are comfortable diving into a large ML codebase to debug. Thrive in a dynamic and technically complex environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI 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

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 The Core Services team is responsible for building and managing foundational services. It acts as the bridge between core infrastructure (e.g. compute, storage, networking) and product engineering teams, and enables product teams to move fast, build reliably, and scale efficiently. About the Role As a software engineer in the core services team, you will design and operate critical backend platforms such as caching systems, workflow orchestration, metadata stores, and file services. You’ll focus on building highly reliable, scalable, and performant systems that serve as the backbone of our products. We’re looking for people who are passionate about building infrastructure that empowers product teams, love working on distributed systems challenges, and enjoy creating well-designed APIs and abstractions that accelerate development. 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: Design, build, and maintain shared infrastructure services such as caching layers, workflow orchestration (Temporal), metadata stores, and file storage services. Collaborate with product teams to provide scalable, reliable primitives that abstract the complexities of distributed systems. Improve performance, resilience, and scalability of core services that power customer-facing applications. You might thrive in this role if you: Have experience with distributed systems, caching infrastructure (e.g., Redis, Memcached), metadata storage (e.g., FoundationDB), or workflow orchestration (e.g., Temporal, Cadence). Have experience running containerized services in cloud environments and integrating them into automated build/test/release (CI/CD) workflows. Understand trade-offs in consistency models, replication strategies, and performance optimization in multi-region systems. Excel at communication and collaboration with cross-functional teams, and are obsesse