System Performance Engineer in France

This role is part of Datadog’s Security Agent team, which powers critical security capabilities across Workload Protection, Vulnerability Management, Cloud Security products, and other emerging security offerings. As a Staff Software Engineer, you will lead the design and development of low-level Linux instrumentation and runtime security technologies that help customers detect threats, monitor system activity, and protect cloud-native workloads at scale. You will work on complex technical challenges involving eBPF, Linux kernel internals, performance-sensitive systems, and large-scale data collection while influencing technical direction across multiple product teams. This role offers significant ownership, broad organizational impact, and the opportunity to shape the future of Datadog’s security platform. 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 architecture and development of security agent capabilities that power runtime threat detection and workload protection across Datadog Security products. Design and build reusable eBPF-based monitoring functionality for process, file, and network visibility within Linux environments. Drive end-to-end delivery of new features, from technical strategy and design through implementation, testing, and rollout. Establish and evolve testing methodologies that improve platform coverage, detection quality, reliability, and performance. Partner with product, security, infrastructure, and engineering teams to deliver shared platform capabilities used across multiple Datadog products. Provide technical leadership by influencing engineering direction, mentoring peers, and helping resolve complex cross-functional challenges. Who You Are: You have significant experience building software in Linux environments,

This role is part of Datadog’s Security Agent team, which powers critical security capabilities across Workload Protection, Vulnerability Management, Cloud Security products, and other emerging security offerings. As a Staff Software Engineer, you will lead the design and development of low-level Linux instrumentation and runtime security technologies that help customers detect threats, monitor system activity, and protect cloud-native workloads at scale. You will work on complex technical challenges involving eBPF, Linux kernel internals, performance-sensitive systems, and large-scale data collection while influencing technical direction across multiple product teams. This role offers significant ownership, broad organizational impact, and the opportunity to shape the future of Datadog’s security platform. 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 architecture and development of security agent capabilities that power runtime threat detection and workload protection across Datadog Security products. Design and build reusable eBPF-based monitoring functionality for process, file, and network visibility within Linux environments. Drive end-to-end delivery of new features, from technical strategy and design through implementation, testing, and rollout. Establish and evolve testing methodologies that improve platform coverage, detection quality, reliability, and performance. Partner with product, security, infrastructure, and engineering teams to deliver shared platform capabilities used across multiple Datadog products. Provide technical leadership by influencing engineering direction, mentoring peers, and helping resolve complex cross-functional challenges. Who You Are: You have significant experience building software in Linux environments,

We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. 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: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You have worked extensively with multiple types of data stores You have contributed to in

Please note that the job is only available from the locations outlined. We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. 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: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You

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

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

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

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

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 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

Observability Pipelines (OP) is Datadog's on-premise, vendor-agnostic telemetry pipeline product. As an Engineering Manager on the team, you'll own people management and engineering execution for one of OP's core missions, spanning areas like Integrations (ingesting from and routing to the many source and destination systems customers rely on), streaming insights, cost control, or pipeline capabilities, reliability and scalability. You'll partner directly with Product to help shape the roadmap, and work closely with your peer EMs and senior ICs to define how OP operates and grows. This is an opportunity to build your management craft while having real influence over the technical direction of a fast-growing product area. 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: Own people management and engineering execution Establish a strong operating rhythm for the team Drive high standards for on-call rotations and incident response Partner with Product on the roadmap, balancing product priorities with technical realities Lead, coach, and grow the careers of engineers on your team Who You Are: Experienced managing engineers directly, comfortable owning a team’s operating rhythm end-to-end, from planning through execution and stakeholder communication to incident and on-call ownership Have a technical background in distributed systems and data infrastructure Have experience with on-premises or customer-installed software concepts A product-minded partner to have on the team — you enjoy working with Product on strategy Experience with high-performance or Rust-based data pipeline systems Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications o

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? Contribute in and provide strong support for model training pipelines, ship state of the art models to production, and bridge the gap between research and production. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and supporting our research effort depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role. As a Member of Technical Staff, you will: Design and write high-performant and scalable software for training. Improve our training setup from an infrastructure and codebase performance standpoint. Craft and implement tools to speed up our training cycles and improve the overall efficacy of our training infrastructure Research, implement, and experiment with ideas on our supercompute and data infrastructure

Source Code Integration enables Product teams at Datadog to develop features that leverage our customers’ source code. This brings the platform closer to developers, as it helps them relate their telemetry to code to run automated investigations, debug their services with stack traces and profiles, scan their code for security issues, or make proactive fixes, among others. The team owns all the platform services, infrastructure and integrations required to access and synchronize our customer repositories in a secure, reliable and efficient manner. We are looking for a hands-on technical leader to drive the growth of our platform, as Datadog shifts left and becomes more developer-friendly and AI-ready. In this role you will lead the growth of our platform to support an increasing number of high profile features and teams, and work with a team of engineers of varied experience levels to shape our roadmap and deliver impactful solutions at scale. 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: Lead and cultivate a team of engineers of diverse experience levels, including performance management and career development Lead technical and strategical discussions to better understand the challenges and opportunities faced by our team and our stakeholders Own and drive the relationships with product teams and major stakeholders, balancing competing requests with long term investments, and prioritizing impact across the whole platform Run a lightweight process to pace and track what we work on. Support the progressive delivery of high quality work through demos and frequent iteration Stay in touch with your team’s systems, and roll up your sleeves when needed to unblock your team by writing code or troubleshooting issue

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

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role Notion is reimagining how customers adopt, expand, and realize value from software in an AI-native world. As a first-line leader directly managing a team of Outcomes Architects, you’ll own your team’s execution across workflow adoption, value realization, renewal readiness, expansion qualification, and at-risk account recovery — accountable for both the customer outcomes and the quality of execution that produces them. This isn’t a traditional Customer Success management role. The best OA Managers are coaches first: they know what great workflow discovery looks like, can review a mutual success plan and identify where value realization is breaking down, can inspect an executive business review and sharpen the value narrative, and can help an OA turn account activity into measurable customer and commercial outcomes. You’ll run an inspection cadence and cultivate a coaching culture that make consistent execution possible across the team. You’ll partner closely with Solutions Consultant leaders, Sales, Services, Support, Product, and RevOps to ensure customers move from workflow design to adoption, value realization, expa