Datadog Notebooks provide customers with a collaborative surface for ad-hoc data analysis, technical documentation, incident postmortems and runbooks. The power and flexibility of Notebooks also makes it the perfect place to integrate AI tools that can augment user workflows. Our vision is that in Notebooks users can collaborate with each other and with AI agents seamlessly. We are looking for a product-oriented Senior Software Engineer to help build the AI-assisted workflows that are becoming central to how customers use Notebooks. In this role you will work closely with product and design, and own platforms for analysis workflows and context discovery. There is a real opportunity for impact here: turning Notebooks into the tool that helps customers go from uncertainty to answer, and making that knowledge retrievable and reusable across Datadog products. 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 design and delivery of AI-powered product experiences for Notebooks and adjacent surfaces Develop systems that combine deterministic product capabilities with LLM-powered experiences to deliver trustworthy and explainable customer outcomes Partner closely with Product: Work hand-in-hand with the Product Manager to translate customer problems, adoption signals, and roadmap goals into concrete technical decisions and iterations Build experiences that enable Datadog capabilities to operate within third-party AI platforms, agents, and conversational environments Provide technical leadership and mentorship while helping establish AI engineering best practices Own production systems: Build and operate reliable backend services that run in the critical path of customer deployments, and be on-call for those services Who You Are You have exper
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Systems Analyst in France
15 active opportunities · Updated September 2026
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Datadog Notebooks provide customers with a collaborative surface for ad-hoc data analysis, technical documentation, incident postmortems and runbooks. The power and flexibility of Notebooks also makes it the perfect place to integrate AI tools that can augment user workflows. Our vision is that in Notebooks users can collaborate with each other and with AI agents seamlessly. We are looking for a product-oriented Senior Software Engineer to help build the AI-assisted workflows that are becoming central to how customers use Notebooks. In this role you will work closely with product and design, and own platforms for analysis workflows and context discovery. There is a real opportunity for impact here: turning Notebooks into the tool that helps customers go from uncertainty to answer, and making that knowledge retrievable and reusable across Datadog products. 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 design and delivery of AI-powered product experiences for Notebooks and adjacent surfaces Develop systems that combine deterministic product capabilities with LLM-powered experiences to deliver trustworthy and explainable customer outcomes Partner closely with Product: Work hand-in-hand with the Product Manager to translate customer problems, adoption signals, and roadmap goals into concrete technical decisions and iterations Build experiences that enable Datadog capabilities to operate within third-party AI platforms, agents, and conversational environments Provide technical leadership and mentorship while helping establish AI engineering best practices Own production systems: Build and operate reliable backend services that run in the critical path of customer deployments, and be on-call for those services Who You Are You have experience with Go,
At 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, enabling 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. APM at Datadog is on its way to redefine how users interact with their telemetry. We are integrating intelligence directly into troubleshooting workflows to help engineers find root causes faster, navigate complex distributed systems seamlessly, and optimize application performance with minimal cognitive load. APM provides deep visibility from end-user interactions to backend services and we are now expanding this foundation with new AI-driven insights, guidance, and automation. As a Product Manager II for APM, you will work with world-class engineers, designers, and partner product teams to shape the future of Distributed Tracing, Performance Analysis, and Intelligent Troubleshooting. You will help build advanced capabilities that scale to thousands of customers and make sophisticated observability workflows accessible to every engineer, from experts to beginners. 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 will Do: Develop a deep understanding of APM customers, their performance challenges, telemetry workflows, and competitors Lead conversations with design partners and strategic customers to uncover real-world performance issues, validate product assumptions, and guide solutions from early prototypes through General Availability Define and deliver the next generation of APM features with engineering and design, especially age
The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection , error outliers and faulty deployment analysis . As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performance You are excited to work on
As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r
As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri
As a Staff Engineer on the Data Platform Experience team, you'll help shape how Datadog engineering teams build, operate, and evolve products on the Observability Data Platform. You'll lead the design and delivery of shared platform capabilities that reduce developer friction, improve operational visibility, and enable engineering teams to move faster with confidence. This role combines deep distributed systems expertise with technical leadership across multiple teams, influencing platform strategy while remaining hands-on in the code. You'll have the opportunity to solve company-wide challenges spanning cost intelligence, operational tooling, platform health, and developer experience. 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 strategic engineering initiatives that improve how product teams build, operate, and evolve services on the Observability Data Platform. Design and build scalable platform capabilities for cost intelligence, including cloud cost allocation, trend analysis, and optimization recommendations. Develop operational intelligence and self-service tooling that helps engineering teams understand platform health, troubleshoot incidents, and improve operational efficiency. Drive reusable platform services and developer workflows that increase engineering autonomy while reducing operational complexity across multiple products. Provide technical leadership across teams by influencing architecture, mentoring engineers, and raising engineering standards through hands-on technical contributions. Participate in the team's on-call rotation and continuously improve platform reliability, observability, and operational excellence. Who You Are: You have experience designing and building large-scale SaaS or cloud platforms with deep expertise i
Distributed Systems engineers at Datadog design, implement and run in production the foundational platforms powering our applications. Your data pipelines will ingest, store, analyze and query in real-time billions of events per second from companies all over the globe. The platforms are optimized for durability, high availability, low latency, internet-scale footprint and operability. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Build fault-tolerant, horizontally scalable solutions running in multi-tenant environments Write in Go, Java, Rust or C++, amongst other languages Use Kafka, Redis, Cassandra, Elasticsearch and other open-source components Own meaningful parts of our service, have an impact, grow with the company Who You Are: You have a BS/MS/PhD in a scientific field or equivalent experience You have significant backend programming experience in one or more languages (Go, Java, Rust, C++) You have been exposed to working on problems (high durability / low latency /…) You can get down to the low-level when needed You care about simple designs and performance You want to work in a fast, high-growth startup environment that respects its engineers and customers You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how You have demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output Bonus: You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you
This role will join Datadog’s Data Visualization organization, a team responsible for the visualization experiences that power dashboards, notebooks, investigations, and product workflows used across the platform. The team is a highly product-oriented organization, building AI-native experiences that help customers understand, investigate, and interact with complex operational data. As a Staff Software Engineer, you will provide technical leadership in applying AI technologies to customer-facing product experiences, helping shape how users interact with Datadog through agents, conversational interfaces, and intelligent investigation workflows. You will partner across engineering and product teams to develop reliable, scalable, and trustworthy AI-powered experiences while helping establish AI engineering expertise within the broader organization. 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 design and delivery of AI-powered product experiences across Datadog’s visualization and investigation surfaces. Develop systems that combine deterministic product capabilities with LLM-powered experiences to deliver trustworthy and explainable customer outcomes. Drive innovation in context engineering, prompt engineering, evaluation frameworks, and AI application reliability. Partner with product and engineering teams to improve investigation workflows and help customers discover insights more efficiently. Build experiences that enable Datadog capabilities to operate within third-party AI platforms, agents, and conversational environments. Provide technical leadership and mentorship while helping establish AI engineering best practices across the Data Visualization organization and broader Graphing group. Who You Are: You have extensive softw
As organizations rapidly adopt AI applications and agentic systems, security teams need visibility and control over how these technologies are being used. Datadog's AI & Data Security product helps customers discover, secure, and govern AI usage across their environments ensuring sensitive data is properly managed from model training through production. As a Product Manager II for AI & Data Security, you will own capabilities for AI discovery, posture management, and data security; giving customers complete visibility into their AI applications, agents, and enabling ecosystem, with prioritized actions to operate AI systems securely. You'll partner with engineering, design, security research, and GTM teams to define and ship platform capabilities that help organizations adopt AI at scale. 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: Own the roadmap for AI & Data Security capabilities, including AI and data discovery & posture management. Define how security teams can assess and manage the security posture of AI-enabled systems, including configuration risks, sensitive data exposure, and policy violations. Work closely with engineers and designers to deliver new product capabilities end-to-end, from early concept through launch and iteration. Partner with Datadog security researchers to identify emerging risks in AI systems and translate them into actionable product features. Engage with customers to understand how they are adopting AI and validate solutions that help them operate these systems securely. Collaborate with go-to-market teams to enable adoption and communicate the value of AI security capabilities to customers. Who You Are: You have 3+ years of product management experience building technical products, ideally in security,
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 with trillions of data points per day, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams for tens of thousands of companies globally. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team The Datadog Security Libraries team owns the customer-side integrations behind our run-time security products App & API Protection , Workload Protection , and Code Security . Our libraries let customers automatically manage application security risk with continuous, real-time monitoring of vulnerabilities and threats against their web applications, serverless applications, and APIs, in production. Automatically integrated with Application Performance Monitoring (APM) distributed tracing and code-level context, our software empowers development, operations, and security teams to build and run secure applications. As a polyglot team we ship and maintain the security capabilities of Datadog's tracing libraries across .NET , Java , Go , Node.js , Python , Ruby , and PHP , on top of a shared C++ core and a set of HTTP proxy integrations (primarily Envoy, NGINX, and HAProxy). Our code runs inside thousands of production applications around the world. Recent work spans exploit prevention (RASP) and WAF detections, API Security, code security (IAST and SCA), and AI-assisted ("agentic") onboarding, always measured by real product outcomes and operational telemetry. The Opportunity We're looking for a senior, polyglot engineer to contribute across several of our security libraries, with .NET or Java expertise. You'll design and build security integrations and detection features, take them from prototype to production-hardened, and own them operationally as they instrument thousands of applications. As a se
About the team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based in Seattle. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and measurable
As a Staff Engineer on Datadog's Compute – Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth. 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 technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers. Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale. Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. Who You Are: You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems. You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language. You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure. Yo
We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity The Partner Sales Manager is a "hunter" role focused on accelerating Partner Sourced pipeline and revenue growth within a specific geographic territory. You will be responsible for the end-to-end activation of Value-Added Resellers (VARs) and Managed Service Providers (MSPs), shifting our posture from "partners on paper" to active, strategic revenue generators. With a key focus on SCC in France By driving deep penetration into partner organizations, you will establish a fair exchange of value where partners source new opportunities and are also brought into direct sales motions to provide technical expertise and value add support. What you'll do Pipeline Generation: Drive net-new pipeline through deal registrations, evidenced by high-impact sales plays and industry-specific solutions to our ICP. Strategic Activation: Evolve existing tactical relationships into purposeful and intentional partnerships. Partner Account Penetration: Build senior-level relationships and establish a presence within partner organizations to pivot their sales posture toward New Relic. Sales & Technical Enablement: Coordinate sales and technical enablement to ensure partners are certified and capable of evangelizing the value of Intelligent Observability. Internal Advocacy: Continually coach internal sales teams and leadership on partnering best practices to foster a positive channel culture and increase collaboration. This role requires Fluency in French and English Hunter M
We are building the best platform in the world for engineers to understand, scale, and protect their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, application tracing, and security insights for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way . At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Solve a scaling bottleneck in a critical service Deploy a new feature to production, progressively rolling it out with feature flags Investigate and fix a production issue from a service your team owns Design a way to scale up a service for more traffic With your team, plan the most important projects to work on next Who You Are: You have significant experience in one or more languages You value code simplicity and performance You can design architecture to solve problems at high scale You have a BS/MS/PhD in a scientific field or equivalent experience You want to work in a fast, high-growth startup environment that respects its engineers and customers You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how You have demonstrated ability to use AI coding tools in day-to-day workflows and build, validate, and refine AI-generated output in products You can design AI Backend systems, with awareness of quality, cost, and latency tradeoffs Bonus: You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products Datadog values people from all walks of life. We understand not everyone will meet all
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