Production Engineer Database Operations in France

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

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

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

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

Une entreprise qui transforme le monde qui nous entoure Palantir construit le premier logiciel au monde pour les décisions et les opérations axées sur les données. En fournissant les bonnes données aux personnes qui en ont besoin, nos plateformes permettent à nos partenaires de développer des médicaments vitaux, de prévoir les perturbations de la chaîne d’approvisionnement, de localiser les enfants disparus, etc. Le poste La plateforme Palantir est déployée dans de nombreux environnements de missions critiques, y compris les zones de combat et les réseaux classifiés, de l’arrière d’un Humvee au cloud, en passant par un poste de commandement. Cela signifie opérer dans différents environnements cloud, dans des réseaux isolés physiquement sur site et en périphérie, à grande échelle. Nous recherchons des ingénieur(e)s d’infrastructure Edge pour développer, exploiter et maintenir des services hautes performances, évolutifs et fiables pour notre infrastructure de production. Ce rôle exige une attention particulière aux systèmes bas niveau, y compris le déploiement et la gestion de serveurs physiques « bare metal » dans des centres de données traditionnels et des environnements Edge. Vous serez responsable de l’ingénierie physique du réseau et du développement d’une infrastructure robuste pour garantir les performances de la plateforme Palantir. En plus d’assurer la performance et la fiabilité, vous jouerez un rôle essentiel dans le développement et la mise à l’échelle de nouveaux environnements dans une capacité de déploiement avancé, y compris sur site. Les ingénieur(e)s d’infrastructure Edge combinent une expérience d’ingénierie au niveau du matériel avec la volonté d’améliorer les systèmes existants et la créativité nécessaire pour développer de nouvelles solutions afin de relever des défis en constante évolution. Notre équipe s’efforce d’automatiser les processus dans la mesure du possible en utilisant les outils les mieux adaptés. Nous croyons fermement que les équ

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

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

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,

We are looking for a strong technical leader to join the Private Action Runner team, part of the larger Action Platform group and help shape one of the core execution layers behind Datadog’s action-taking and remediation capabilities. Private Action Runner (PAR) enables Datadog products and AI agents to securely run actions inside customer infrastructure with controls for authentication, permissions, auditing and safe execution. The role will be hands-on, covering architecture, implementation, reliability and collaboration with teams integrating PAR across Datadog. It also offers leadership exposure through leading a team of 3 engineers, with the expectation that the role will quickly transition into a formal Engineering Manager 1 position as the team grows. 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: (Describe role responsibilities here) 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 Mentor and lead a small team of 3 engineers Who You Are: (Describe role qualifications here) 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

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

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

As a Network Engineer II on the Office Technology team, you will implement and support office network solutions across Datadog’s global offices. You will own well-scoped deployment and upgrade work, troubleshoot connectivity issues across LAN, WAN, and Wi-Fi, and partner with senior engineers on larger designs and cross-office initiatives. You will collaborate closely with vendors, Facilities, AV, IT Support, Security, and Infrastructure teams to keep Datadog offices connected, reliable, and observable. This is an IC2 role with a mix of project work and day-to-day operations. You will take ownership of clearly defined areas of the office network stack, execute production changes with care, and grow your ability to design, automate, and improve office network services with support from senior engineers. You will also use AI-assisted tools responsibly to improve troubleshooting, documentation, automation, knowledge discovery, and operational follow-through. 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: Deploy and configure network solutions for new and existing offices, including switches, wireless access points, routers, and firewalls Own scoped portions of office rollouts and upgrade projects, from planning through execution and validation Partner with ISPs, cabling providers, hardware vendors, and internal teams to turn up new services and resolve issues Troubleshoot LAN, WAN, and Wi-Fi issues using structured debugging methods, packet capture, logs, and performance data Manage routing, VLAN, firewall, and wireless configurations following team standards and change-management processes Contribute to repeatable deployment patterns through templates, documentation, scripting, or infrastructure-as-code Monitor office netwo

Applied AI is where Datadog's ambitious AI bets get built and shipped ( Bits Chat , updog ). We sit at the intersection of research and product: turning promising capabilities from Datadog AI Research lab and the research community into production systems that reach real customers. The team builds specialized models that replace frontier models where they are not necessary, making AI capabilities faster, cheaper, and more secure. The mandate is to move fast from idea to customer impact, and when a product finds its footing, to set it up for growth. As a Manager I in Applied AI, you will lead a team of engineers and applied scientists working on one of these challenges. You will define technical direction, run short feedback loops, make deliberate decisions about what to pursue or stop, and work closely with product managers, research teams, and cross-functional partners to ship AI capabilities that matter. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. 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 and develop a team of engineers and applied scientists focused on cost-efficient specialized models and AI security capabilities Work closely with product managers, research teams, and cross-functional partners to shape the team's bets from initial framing through to broader adoption, with a clear definition of success criteria at each stage Own end-to-end delivery of high-quality AI systems, from early research exploration to production-grade reliability, with high standards for operational excellence, system reliability, and technical quality Navigate the unique challenges of shipping AI-powered products: balancing quality, latency, cost, and safety considerations. Drive evaluation and iteration practices for AI systems: define the quality bar and guide the team in building the offline

The Security Libraries team owns the customer-side integrations behind Datadog’s run-time security products — App & API Protection , Workload Protection , and Code Security — shipping and maintaining security capabilities across seven open-source language libraries ( .NET , Java , Go , Node.js , Python , Ruby , PHP ) and a set of HTTP proxy integrations (Envoy, NGINX, and HAProxy), running inside thousands of production clusters worldwide. Recent work spans exploit prevention (RASP), WAF detections, API Security, code security (IAST and SCA), and AI-assisted onboarding. As Engineering Manager, you’ll lead part of this polyglot team, setting the technical bar and team culture while driving the pace at which new detections and AI-assisted capabilities reach customers. This is a hands-on role: you’ll balance people leadership, product and roadmap ownership, and the operational health of code that runs in production at massive scale, with room to grow into more of Datadog’s security portfolio over time. 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, grow, and develop a team of roughly 4-8 library engineers — coaching, giving direct feedback, and empowering senior ICs as technical leaders Own team delivery and productivity: planning, milestones, reviews, and the on-call rotation Set product direction with Product Management and balance priorities across App & API Protection, Workload Protection, and Code Security Stay technically close to the work — apply strong technical judgment, contribute code where it matters most, and keep quality and architecture high Build strong relationships and drive alignment across the language teams and product, backend, and frontend partners Shape team identity and culture, and own accountability when problems oc