Systems Engineering Intern in France

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

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 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 an Enterprise Sales Engineer, you'll partner with Sales to help customers understand the value of Datadog and how it solves their most important technical and business challenges. You'll lead technical evaluations, deliver compelling demos, and guide customers through the journey from discovery to successful adoption. You'll act as a trusted advisor, bridging business goals with technical solutions, and play a key role in winning new business and expanding existing accounts. What You’ll Do: Own the sales process in partnership with Account Executives by leading and shaping the technical strategy across opportunities from PG to Closed Won Lead customer discovery to uncover technical challenges, business goals, and success criteria, then translate those needs into tailored Datadog solutions Deliver engaging product demos, technical presentations, and workshops that connect platform capabilities to customer outcomes Project manage technical evaluations (POVs) end-to-end: scoping use cases and requirements, defining success criteria, building a project plan with clear timelines, and holding all participants accountable to the process Identify and cultivate technical champions within customer accounts, empowering them to advocate for Datadog adoption and drive consensus internally Participat e actively in structured product and engineering field feedback sessions, serving as the technical voice of the customer to help shape product direction Maintain operational excellence by ensuring activity, deal progress, and customer interactions are accurately documented and up to date in related systems Collaborate cross-functionally with Product, Support, and GTM teams to address customer needs and resolve technical blockers Who You Are: 5+ years of experience in Sales Engineering, Solutions Engineering, or a technical customer-facing role within an enterprise environment Skilled at navigating multi-stakeholder environments and adapting communication style t

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,

The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI , LLMObs and all our AI research . As an engineering manager for the Training & Serving team, you’ll join a new and fast growing team and organization. You will support building and scaling the team, define our technical vision and help shape the roadmap. Your team will lead the charge on multiple critical technical challenges: distributed training of foundation models, serving at scale, designing the user experience. You’ll work closely with sister teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org and with Datadog infrastructure & tooling teams to build out systems from the ground up. 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: Manage and grow the Training & Serving team, directly managing 10+ engineers Define our technical roadmap in alignment with AI platform goals and the Applied AI team roadmap. Work with our core platform teams to tailor Datadog's storage, infrastructure and data pipelines to our needs Create a strong team culture aligned with our engineering standards and our customer focus Participate in hands-on work: Code reviews, design reviews and some coding Who You Are: Previous experience (1+ years) leading software engineering teams, as a tech lead or people manager Strong technician with a mix of backend, data engineer and infrastructure experience who is interested in remaining a hands-on leader Excellent leader with strong

The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI , LLMObs and all our AI research . As an engineering manager for the Evaluation & Annotation team, you’ll join a new and fast growing team and organization. You will support building and scaling the team, define our technical vision and help shape the roadmap. Your team will lead the charge on multiple critical technical challenges: AI model evaluation both offline and online, designing tooling and processes around human annotation, and establishing the standard around synthetics and AI generated datasets. You’ll work closely with sister teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org and with Datadog infrastructure & tooling teams to build out systems from the ground up. 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: Manage and grow the Evaluation & Annotation team, directly managing 4-6 engineers Define our technical roadmap in alignment with AI platform goals and the Applied AI team roadmap. Work with our core platform teams to tailor Datadog's storage and data pipelines to our needs Create a strong team culture aligned with our engineering standards and our customer focus Participate in hands-on work: Code reviews, design reviews and some coding Who You Are: A Software Engineer at heart with a previous experience leading software engineering teams, as a tech lead or people manager Excellent leader with strong interpersonal skills, and the

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

Data Semantics is Datadog’s authority on semantic knowledge, providing shared infrastructure that powers both Datadog’s product experiences and AI capabilities. As Datadog continues its investment in OpenTelemetry-native observability, semantic interoperability, and AI-powered workflows, this team sits at the center of some of the company’s most strategic platform initiatives. As a Staff Engineer, you will serve as a technical leader for the team, balancing stewardship of critical production systems with the exploration of new platform capabilities that improve how telemetry is modeled, understood, and consumed across Datadog. You will work closely with engineering and product partners to define standards, drive technical direction, and deliver solutions that scale across Datadog’s observability 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 technical direction of the Data Semantics team while remaining deeply hands-on in design, implementation, and delivery. Build and scale semantic infrastructure that bridges OpenTelemetry, Datadog-native telemetry, cloud-provider telemetry, and customer-defined data models. Drive platform initiatives focused on schema evolution, telemetry standardization, data insights, and semantic interoperability across Datadog products. Partner with engineering and product teams across the platform to define standards, align stakeholders, and deliver high-leverage platform capabilities. Mentor engineers through design reviews, technical guidance, operational excellence, and long-term career development. Participate in on-call rotations and lead investigation and resolution efforts for complex production incidents affecting critical platform services. Who You Are: You have significant experience designing, opera

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

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! The integration team is responsible for developing and scaling machine learning algorithms and infrastructure for LLM post-training, with a focus on large-scale, distributed RL methods. We strive for excellence in both engineering and science by meticulously designing experiments and design docs. While tasks are assigned according to everyone’s expertise, there is a global team effort to write production code and support the team research efforts, depending on individual interests and organizational needs. In particular, this role aims to enhance the global quality of the post-training codebase by implementing new tools to ease and support research, optimizing post-training algorithms, and scaling distributed RL to unprecedented levels. Please Note: We have offices in London, Paris, Toronto, San Francisco, New York but we are also remote-friendly! Applicants for this role may work anywhere between UTC−06:00 and UTC+01:00. As a Member of Technical Staff, you will: Design and write high-performing and scalable software for training models. Develop new tools to support and accelerate research and LLM training. Coordinate with other

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

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

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