Cloud Devops Engineer in France

As a Senior Product Manager for AI & Data Security at Datadog, you will define and deliver capabilities that help organizations securely adopt and scale AI across their applications and infrastructure. You’ll focus on building products that provide visibility into AI systems and data usage, assess security posture, and enable teams to manage risk across the AI lifecycle. This role sits at the intersection of security, AI, and cloud platforms, and is ideal for a PM who thrives in emerging, ambiguous problem spaces. You will work cross-functionally to shape how customers discover, understand, and secure AI-powered systems in production. 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 and drive the roadmap for AI & Data Security capabilities, including data security posture management and data loss prevention Define how customers assess and manage the security posture of AI systems, including risks related to configuration, data exposure, and policy compliance Partner with engineering and design to deliver end-to-end product capabilities, from concept through launch and iteration Collaborate with security research teams to identify emerging risks in AI systems and translate them into actionable product features Engage with customers to understand AI adoption patterns and validate solutions that enable secure, scalable operations Define and track success metrics such as product adoption, usage, and impact on customer security workflows Who You Are: &l

As a Platform Security Engineer you will partner with different stakeholders across the organization to secure our infrastructure and application components of the Datadog platform. As part of the Platform Security organization we secure the building blocks of Datadog’s applications and infrastructure. We do this by building solutions solving systemic risks making the secure path easier and the insecure path harder. 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 our most challenging cloud infrastructure security & application security problems starting with our core building blocks and golden paths. Enable our engineers to build and ship secure solutions quickly. Build and extend Datadog’s Platform Security solutions. Leverage and influence the direction of Datadog’s products to secure our infrastructure, and provide internal feedback that enables our teams to improve the products for ourselves and our customers. Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent professional experience. You don’t want to just provide security recommendations, you want to help implement solutions to solve systemic issues. Passionate about advocating for and implementing solutions to complex security problems, at-scale, in a large multi-cloud self-managed Kubernetes environment. Proven experience in securing enterprise SaaS applications including securing the underlying authentication flows, authorization patterns, and input validation at API boundaries. Demonstrated experience in securing the deployment & management mechanisms for software and infrastructure changes. Familiarity with common security frameworks such as OWASP, MITRE ATT&CK, PAST

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

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Solutions Architect in GitLab's Southern Europe team with particular focus on France, you'll be a trusted advisor to GitLab prospects and customers, helping them understand how GitLab's DevSecOps platform addresses both technical requirements and business objectives across the entire software development lifecycle. You'll guide organizations through their digital transformation journeys, from planning through monitoring, using your technical expertise, understanding of cloud and modern software development practices, and strong customer empathy. Reporting to a regional Solutions Architect manager and

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 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

Datadog (NASDAQ: DDOG) is looking for a Product Strategy and Corporate Development Lead to drive Product vision, M&A, and venture investments for Datadog. You will work directly with Datadog's founders, partnering with Datadog's global engineering and product leaders to identify and execute transactions that expand our platform into new markets. This is not a traditional Corp Dev seat. You will operate on a small, high-autonomy team where technical depth matters as much as deal execution. You can expect to focus on the EMEA landscape, which is one of the most dynamic ecosystems in enterprise software right now, and you will be at the center of it. At the same time, you'll be working with our Product and Engineering leaders based in Europe, who will depend on you to be the fabric between our NYC and Paris HQs. Together, you'll be expected to go deep and autonomously explore new areas of expansion for us. 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) Be close to our Product & Engineering leaders to discover new areas of interest and acceleration before an M&A target is even identified, and stay ahead of market trends in AI/ML, observability, security, and cloud infrastructure to inform Datadog's growth strategy Identify and evaluate M&A targets and venture investment opportunities across European markets, with a focus on AI-native and infrastructure companies Build deep relationships with founders, VCs, and accelerators across the Paris, London, and Iberian ecosystems to generate proprietary deal flow Lead end-to-end due diligence: technical product assessments, financial modeling, valuation analysis, and integration planning Partner with senior engineering and product leaders to assess techni

MongoDB's Application Modernization Platform (AMP) team aims to grow the adoption of MongoDB by accelerating the rate at which legacy applications built on RDBMS can be modernized to MongoDB. The AMP team uses a combination of proprietary GenAI and deterministic tools combined with modernization techniques (methodologies) developed over numerous customer engagements to modernize legacy applications to MongoDB. This involves modernizing both the application tier by decomposing the legacy application into services and building modern services on MongoDB. Our modernization methodologies involve apply specialized tools that automate a wide variety of modernization tasks including analyzing legacy code bases to figure out how to disaggregate them, transforming legacy code (PL/SQL, T-SQL, Java, C#) to modern application frameworks on MongoDB, automated test generation, and side-by-side testing (legacy vs. modern). We are looking for a Solutions Architect to support the sales and delivery of modernization engagements. This role will be based remotely in France. Roles Responsibilities Ideally 8 to 11 years of related experience in a customer facing role, with 5 to 7 years of experience in pre-sales with enterprise software Minimum of 3 years experience with modern scripting languages (e.g. Python, Node.js, SQL) and/or popular programming languages (e.g. C/C++, Java, C#) in a professional capacity Experience with modern software development processes and application architectures including (not an exhaustive list): agile development, domain driven design, microservice architectures, test-driven development, event-driven architectures, operational data layers, test automation, etc. Experience designing with scalable and highly available distributed systems in the cloud and on-prem Facilitate technical workshops and discovery sessions with customer architects, developers, and business leaders Experience installing and delivering complex demonstrations consist