At Datadog, we process millions of monitors every minute, alerting our customers when configured thresholds are crossed. Engineers across the world trust us to alert them when necessary, so our Alerting stack needs to be reliable and scalable. The Alerting Platform Automation team’s main goal is to improve the processes and tooling that let our Alerting developers operate the platform efficiently. We design and operate automation systems that replace manual actions, from creating environments to deploying and testing safely. We build test environments that give engineers and their AI coding tools fast, reliable feedback, so changes can be validated in minutes rather than days. Our team is looking for a Senior Software Engineer to help us maintain and scale the Alerting platform. In this position, you’ll work daily with our users, understanding their needs, defining solutions, building the necessary tooling and communicating with all our stakeholders appropriately. 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 automation systems that create and manage Alerting environments, with a focus on fast, realistic test environments that shorten the feedback loop for engineers and AI-assisted development workflows. Work with SRE, Core Infrastructure and the Alerting engineering teams to understand their needs and provide solutions. Lead infrastructure projects and improve our CI/CD and developer tooling, including our deployment process. Identify reliability bottlenecks, then design solutions to mitigate or eliminate them, including load testing and testing of infrastructure configuration before it reaches production. Improve infrastructure isolation and make our services scale automatically with load. Who You Are: You’re interested in ops and infrastructure challenges, and you’re comfortable writing the code that automates them. You can analyze a problem, identify its root cause and propose short-term and long-term solutions. You’re a team player, able to work easily with your team members and with many other development teams. You communicate appropriately to your audience, from fellow devs to top management. You work autonomously across multiple technologies owned by different teams, and you like to discover and learn new ones. You think that infrastructure and code are equally important. You’re curious about how AI-assisted development changes the way we build and test software, and you enjoy making tooling that works well for both humans and agents. 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’re passionate about technology and want to grow your skills, we encourage you to apply.

Senior Software Engineer - Distributed Systems (ODP Governance) ODP Governance is a cross platform team working in the biggest Datadog products (Metrics, Logs, APM) with the mission of giving customers governance tools to control costs and data hygiene of their telemetry. Our team builds cost controls and governance tools that help Datadog’s enterprise customers manage data ingestion, reduce unwanted data, and prioritize the telemetry that delivers the most value. Our scope spans multiple Datadog products, including Metrics, Events, Logs, and APM. As a backend engineering team, we partner with these product teams to address recurring customer challenges that create operational friction, increase costs, and contribute to churn. We also identify opportunities to extend successful capabilities across products—for example, adapting a control developed for Logs to support APM.   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 performant high scale distributed systems to handle the load of Datadog’s biggest products Build relationships across teams and independently seek out the information needed to move work forward. Become productive in unfamiliar systems and navigate ambiguity. Anticipate technical dependencies and integration challenges early. Recognize when a solution could benefit another product and take the initiative to explore it. Connect engineering decisions to customer value, cost efficiency, and usability. Who You Are: You have 6+ years of experience You have significant backend programming experience in one or more languages (Go, Java, Rust, C++)  Distributed systems engineer with experience building high performance large scale systems.  Excellent communication skills (English). High proactivity and cross-team collaboration experience 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’re passionate about technology and want to grow your skills, we encourage you to apply. 

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 occur Who You Are: Experience managing a team of engineers — setting direction with Product Managers, owning a backlog, and running delivery A senior software-engineering background with strong technical judgment A track record developing people: coaching, direct feedback, and helping engineers, both senior and struggling, grow Strong cross-team communication, comfortable driving alignment across many stakeholders Experience building libraries, SDKs, developer tooling, or systems/run-time software Pragmatic product-engineering experience — you’ve worked with Product Managers and weighed technical trade-offs against customer impact Nice to Have: An application security background (WAF, RASP, IAST/SCA) or adjacent observability/APM experience Hands-on experience with one of our languages (.NET, Java, Go, Node.js, Python, Ruby, PHP) or open-source stewardship Experience leading distributed or multi-language teams across many stakeholders 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’re passionate about technology and want to grow your skills, we encourage you to apply.

Application Performance Monitoring (APM) is one of Datadog’s premier products that helps developers see inside complex distributed systems. Our SDKs are both the delivery vehicle for APM and the platform on which all of Datadog’s service and app based products (e.g. Application Security Management, Profiling, Data Stream Monitoring…) are delivered. We believe our SDKs are one of our technical moats and are a key competitive advantage for APM and Datadog more broadly. They’re also open-source. Leading the evolution of our SDKs is a technically demanding and highly collaborative effort. You’ll work with language experts to deliver cutting-edge observability products across our 9 supported languages, with industry leading performance and a world class developer experience. You’ll rethink our SDKs’ architecture, APIs, data models, and protocol to meet Datadog’s current needs and scale, all while building in the open. And you’ll grow your team’s capacity by fostering a culture focused on customer needs, continuous learning, and innovation.  We’re looking for an experienced Engineering Manager who cares as much about technical excellence as empowering other engineering teams.  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, grow, and develop a team of roughly 4-8 library engineers — coaching, giving direct feedback, and empowering senior ICs as technical leaders owning outcomes Own team delivery and productivity: planning, milestones, reviews Collaborate with Product teams to: Reshape and grow our platform capabilities to enable product teams  Define and deliver industry leading, open-source, zero-touch APM instrumentation Stay technically close to the work — apply strong technical judgment, set a high standard for quality, 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 Shape team identity and culture Who you are An experienced Engineering Manager with a track record of shipping  A strong and empathetic leader with the ability to build and lead high-performing teams to deliver high quality software An ability pivot from high level product narratives to highly technical implementation details  You have significant programming experience in one or more of: Go, C, Rust Bonus: If you possess experience with one or more of these skills: systems programming experience, observability tooling experience, experience shipping client side software, Go runtime expertise 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’re passionate about technology and want to grow your skills, we encourage you to apply. 

Datadog's Digital Experience Monitoring (DEM) group is one of the company's fastest-growing product areas, spanning Real User Monitoring (RUM), Product Analytics, Synthetic Monitoring, Feature Flags, and Datadog Studio, our newest AI-native observability surface. As Director, you will own engineering for one or more of these product areas, with scope shaped by your background and interests, and you will manage 50-60 engineers through a team of Engineering Managers. You'll partner with Senior Directors and product leadership to shape the roadmap, not just execute against it, and you'll help drive AI adoption across engineering tooling, workflows, and product features. This role is based in Paris, one of Datadog's most established engineering hubs, with a clear growth path to Senior Director for the right candidate. 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 engineering for one or more DEM product areas with scope calibrated to your background and strengths Manage 50-60 engineers through a layer of Engineering Managers; this is a manager-of-managers role Shape the roadmap alongside product leadership rather than simply executing against it — push back on, iterate on, and help author the strategy for your area Drive AI adoption across the engineering org, from tooling and workflows to product features and team practices Navigate cross-team dependencies across DEM, APM, Core Platform, AI Platform, and Data Science Build and retain engineering talent in Paris, mentor Engineering Managers toward Director readiness, and participate in the on-call rotation   Who You Are: You have directly managed Engineering Managers, not just individual contributors — this is a non-negotiable requirement for the role You integrate AI deeply into how you lead and how your teams build, treating AI-first thinking as core engineering practice rather than a feature bolted onto the product You have a track record of shaping product decisions, not just executing against a spec You've worked with large-scale, event-driven or data-intensive backend systems — ingestion pipelines, high-throughput APIs, or time-series/event data at scale You bring full-stack or frontend-adjacent experience; DEM is an SDK-heavy, browser- and mobile-facing product group You're comfortable operating in English in a cross-Atlantic org, and are based in Paris or open to relocating there (French is not required)   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're passionate about technology and want to grow your skills, we encourage you to apply.  

Datadog’s Chaos Engineering team builds systems that surface reliability weaknesses before they become outages. As a Senior Software Engineer, you will initially focus on zonal resilience, building automation that helps services safely evacuate and recover from zonal failures, while also contributing to fault injection, incident replay, gameday orchestration, and reliability tooling. You will work across engineering teams to design systems that safely exercise production failure modes and turn findings into verified remediation. You will also help advance the use of AI and automation to identify, test, and close resilience gaps as Datadog’s software and infrastructure evolve. 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 zonal-resilience automation that coordinates safe workload evacuations, switchovers, and recovery in partnership with the teams that own affected services. Design and build fault-injection systems for production environments, including infrastructure- and application-level testing, incident replay, and controlled resilience experiments. Develop safeguards such as blast-radius controls, kill switches, validation mechanisms, and rollback paths that keep production experiments contained and reversible. Build agents and automation that help propose failure scenarios, triage experiment results, and connect reliability findings to tracked remediation and verification. Lead gamedays from hypothesis and scenario design through execution, documented findings, remediation tracking, and validation of completed fixes. Design and implement reliable distributed systems, including gRPC services, Kubernetes controllers, and shared platform components, while contributing to technical design and mentoring other engineers. Who You Are: You have strong distributed systems fundamentals and can reason about consistency, failure modes, backpressure, idempotency, quorum, retries, and failure recovery. You understand Kubernetes workload lifecycles, including how pods, controllers, scheduling, draining, and eviction interact with resilient system design. You have experience designing, building, or operating production systems where safety, availability, and controlled failure handling are important. You communicate complex technical decisions clearly through design documents, runbooks, postmortems, and cross-functional technical discussions. You are comfortable collaborating across engineering teams to understand unfamiliar systems, identify failure modes, and drive resilience improvements. Experience with reliability engineering, chaos engineering, zonal failover, AI-assisted operational workflows, traffic interception, or large-scale observability systems is beneficial but not required. Datadog values people from all walks of life. We know not everyone will meet all the above qualifications on day one. That’s okay. If you’re passionate about technology and want to grow your experience, we encourage you to apply.

The Autonomous Ops & Maintenance (ATOM)Team  is developing an innovative platform that leverages artificial intelligence and automated systems to empower engineering groups in safely executing complex operations and software maintenance. Their primary objective is to minimize repetitive toil while delivering the precise visibility, oversight, and trust necessary to run automated solutions in mission-critical environments. Consider it an intelligent virtual collaborator operating alongside development and infrastructure engineers, directly offloading routine operational overhead that currently requires manual intervention.   We are looking for a Senior Software Engineer to help us design and scale our foundational architecture. In this role, you will synthesize vast technical datasets into rich structured knowledge, engineer AI-driven components capable of analyzing intricate operational workflows, and construct highly reliable systems to execute automated modifications seamlessly.   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 a greenfield initiative from inception to scale, shaping foundational product architecture, engaging directly with users to refine early concepts Build mission-critical solutions that customers depend on daily Build fault-tolerant, horizontally scalable solutions running in multi-tenant environments   Who You Are:    You have 6+ years of experience You have a BS/MS/PhD in a scientific field or equivalent experience You are proficient in Go You are comfortable building and operating production services end to end: You will independently own features and components, work through ambiguous technical problems, and be responsible for the reliability, observability, and operational quality of what you ship You have experience with large scale distributed systems You have demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output Bonus Point: You have experience with Kubernetes, workflow orchestration systems, or building AI agents  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’re passionate about technology and want to grow your skills, we encourage you to apply.  

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. You have hands-on experience with Linux kernel internals (namespaces, cgroups, capabilities, seccomp) and hardening techniques such as KASLR, module allowlisting, or kernel self-protection (KSPP) controls. Experience with virtualization or microVM technologies (KVM, QEMU, Kata Containers, Firecracker, or similar) and the security boundaries a hypervisor provides versus a container. Familiarity with container runtime internals (containerd, OCI runtimes, checkpoint/restore). Demonstrated experience in securing the deployment & management mechanisms for software and infrastructure changes. Familiarity with common security frameworks such as OWASP, MITRE ATT&CK, PASTA/STRIDE, CIS, etc. You have prior experience in Software Engineering, Platform Engineering, Systems Engineering, Network Engineering, Cloud Security or Application Security. Software engineering background with hands-on code review experience; Go, Python, or Rust Experience with one or more Kubernetes PKI & network technologies (Consul, Envoy, Cilium, Vault, Istio, etc.) and eBPF-based tooling. Experience with one of the major cloud providers (AWS, Azure, GCP) and Kubernetes. Able to work both independently and collaboratively, willing to work in a fast paced, high growth environment. You stay updated with modern security best practices, technologies and emerging threats.   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’re passionate about technology and want to grow your skills, we encourage you to apply.   

As a Research Manager within Datadog AI Research (DAIR), you will lead a team working on fundamental research in foundation models and world models while remaining deeply engaged in the technical direction of the work. You will advance large-scale pre-training and multimodal learning across the diverse signals generated by distributed systems, including metrics, traces, logs, topology, and events. You will provide technical leadership to a team of researchers and research engineers, mentor and develop highly technical talent, shape research direction, and collaborate with Datadog’s product and engineering teams to translate research advances into products. This role is designed for an exceptional researcher or technical leader who wants to maintain a strong hands-on research identity while developing and leading a high-performing team. 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 research in foundation models, world models, and multimodal learning, setting the technical direction for ambitious research programs grounded in observability and security Guide and mentor researchers and research engineers while remaining closely involved in research strategy, experimentation, model development, and technical problem-solving Train large-scale multimodal models on diverse telemetry data, including metrics, logs, traces, topology, events, and other non-text modalities Advance approaches to pre-training, representation learning, world modeling, scaling, and evaluation for models that learn the dynamics of complex distributed systems Collaborate with cross-functional teams across Research, Product, and Engineering to translate research advances into scalable Datadog capabilities Contribute to research publications, present at top-tier conferences such as NeurIPS, ICLR, and ICML, and help open-source key model artifacts and benchmarks   Who You Are: You hold a PhD in Computer Science, Machine Learning, or a related field, or have equivalent experience, with deep expertise in areas such as foundation models, world models, multimodal learning, or generative modeling You have demonstrated the ability to lead technically ambitious research at meaningful scale, whether in an industry research lab, startup, academic environment, or another research setting You have extensive hands-on experience designing, training, or evaluating large-scale deep learning models (such as large language models), with experience in multimodal or non-text data considered a strong plus You have a track record of research impact through influential publications, significant model or system contributions, widely used research artifacts, or equivalent technical achievements You have operated at a senior technical level and have experience leading, mentoring, and developing teams of researchers or engineers, while remaining deeply hands-on in technical direction and execution You want to develop and support a research team while maintaining a strong technical identity, and you can communicate complex research findings effectively across technical and non-technical audiences 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’re passionate about technology and want to grow your skills, we encourage you to apply.  

The Enterprise IT Support team is responsible for the hardware and software that Datadog employees around the world use on a daily basis to successfully do their jobs. As an Enterprise IT Support intern, you will combine theoretical learning at your school with practical, hands-on experience in our IT Support team. Over the course of your internship, you will progressively take on more responsibilities while helping ensure our ever-growing user base has everything they need to do their job. You’ll also gain exposure to security-adjacent tasks relevant to IT support operations.  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 Learn and assist in providing customer service and technical support for our employees Shadow and support laptop deployment as part of onboarding and refresh cycles Shadow and support laptop collection and account deactivation as part of employee offboarding cycles Participate in new hire orientations to understand policies, best practices and services used within Datadog Assist with general ticketing, account management, and basic troubleshooting under supervision Help maintain hardware and software inventory Contribute to documentation creation and maintenance Observe and support unified communications setups in conference rooms and common areas Participate in team meetings and knowledge-sharing sessions Gain exposure to deployment and security-related projects Support multi-factor authentication (MFA/2FA) setup and troubleshooting for employees Observe and support endpoint device enrollment using mobile device management (MDM) tools Gain familiarity with access management principles, including the processes used to grant, review, and revoke employee access Assist in following established procedures when responding to basic IT Security incidents under supervision Participate in identity verification processes Develop skills in various SaaS tools and IT workflows   Who You Are: You will graduate in 2027 with a degree in IT, Cybersecurity field This internship is required as part of your academic curriculum You are passionate about technology and eager to learn You love working in a team and helping people You have a basic understanding of computer hardware and software You have great communication skills in English (French is appreciated!) You are curious about how things work and enjoy problem-solving You are available to complete a six-month internship beginning in February, March, April, May, or June 2027. (we are unable to accommodate internships starting at any other time) Datadog values people from all walks of life. We know not everyone will meet all the above qualifications on day one. That’s okay. If you’re passionate about technology and want to grow your experience, we encourage you to apply.

The Incident Insights & Readiness SRE team at Datadog fosters a resilient culture by using incidents as learning opportunities and catalysts for growth. Our users are Datadog engineers, and we build the software, tooling, and operational frameworks that help them prepare for, respond to, and learn from incidents. We work closely with engineering teams across Datadog to analyze incidents and turn those insights into better tools, stronger incident response, and organizational learning. Our efforts empower Datadog to navigate unexpected failures confidently, efficiently, and with a commitment to continuous learning and systems improvement.   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 improve the on-call experience for the company by establishing best practices and building platforms to support on-call rotations and compensation. Define how we respond to incidents, lead the design and implementation of software to streamline the process, and collaborate with product teams to improve incident response across Datadog. Our aim is to fully support our incident responders in dealing with complexity. Contribute to the post-mortem process for the company, collaborating with teams on writing them, and identifying opportunities to reduce friction and enhance learning value for the organization. Our team also runs a weekly postmortem reading group. Support various teams in facilitating incident reviews that emphasize learning and blamelessness. Help them share their learnings across the organization to improve the resilience of our people. Provide technical leadership and day-to-day coaching to team members, accelerating their growth through design reviews, collaborative problem-solving and operational excellence best practices. Train our on-callers in incident and post-mortem processes, sharing expertise in incident management best practices. This involves both introducing newcomers to on-call responsibilities and refreshing the knowledge of existing engineers. Lead cross-functional initiatives in engineering organizations across Datadog, embedding with teams to understand their challenges and drive lasting improvements to reliability and operational excellence.   Who You Are:    At least 5 years of experience building software that solves real user problems. Experience designing new features and collaborating on code and technical design reviews. We primarily develop in Go and Python, with a bit of TypeScript. Experience building or operating distributed systems, with familiarity with Kubernetes and an understanding of complex failure modes. Demonstrated ability to independently own ambiguous technical problems from design through delivery while balancing long-term engineering quality with pragmatic execution. Experience analyzing incidents, identifying systemic risks, and driving engineering improvements informed by operational learnings. Experience participating in on-call rotations and improving incident response processes. Experience serving as an incident commander or incident coordinator is a plus. Empathy, collaboration, and communication skills in English to cultivate strong relationships across various teams in the organization Experience mentoring engineers, driving cross-functional initiatives, and influencing technical direction without relying on organizational authority. We welcome candidates from a variety of backgrounds, including software engineering, site reliability engineering, production engineering, infrastructure, and other roles focused on building reliable systems or improving incident response.   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’re passionate about technology and want to grow your skills, we encourage you to apply.  

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 issues Support both internal and external customers resolve their issues, and find systematic solutions that elevate our platform and integration experience   What we’re looking for:  A good collaborator, an enabler, a natural leader that puts people first A backend engineer at heart, with experience building robust systems composed of multiple services, data streams and stores operating at scale Significant experience with major backend technologies (e.g. Go, Python, or Java, PostgreSQL, Kafka), event driven architecture and or distributed systems Experience running platform services, comfortable making tradeoffs and balancing short term impact with long term sustainability. Proven ability to work closely with product and internal teams to deliver solutions at scale Passion to work in a fast-paced, high-growth environment providing leadership and direction for a highly technical team Positivity and proactivity towards AI. Experience using agentic tools for development and analysis 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’re passionate about technology and want to grow your skills, we encourage you to apply.   

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 and online evaluation pipelines needed to measure quality and detect drift Contribute to cross-team collaboration and knowledge sharing across the broader AI organization Support career growth for engineers through coaching, feedback, and fostering a culture of experimentation, innovation, and learning. Participate in hiring and help shape the future team as the organization grows Who You Are A people-focused manager with experience leading and mentoring engineers, able to develop strong engineering talent in a fast-moving domain A technical leader with deep expertise in one or more areas of AI or machine learning: large language models, retrieval-augmented generation (RAG), semantic search, agentic systems, deep learning, or NLP Well-versed in evaluation methodologies for AI systems, both offline benchmarks and online metrics A strong product instinct: able to anchor early-stage work in concrete customer problems, define success criteria before writing code, and actively contribute to shaping product direction alongside product and research partners Experience taking AI products from 0 to 1 is strongly valued: able to bring structure to early-stage work by scoping clear hypotheses, moving quickly toward signal, and making deliberate decisions about what to pursue, pivot, or stop BS/MS/PhD in Machine Learning, Computer Science, Engineering, or related field, or equivalent professional experience #LI-Hybrid About Datadog:  Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.  Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.  Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

The Behavior AI team builds the AI-based anomaly detection behind Datadog's security products. Our models learn what normal looks like across the billions of logs, events, and telemetry records flowing through the platform every second, and they flag the behavior that does not fit, on every record, in real time, at a cost that makes sense at our scale. What we build does not ship to a single feature. The same models power detection across many of Datadog's security products at once, so the work has impact well beyond any one team. Large general-purpose models are too slow and too expensive to run in that path, so we take the opposite approach: small, custom models, designed for high-throughput stream processing and optimized to run cheaply on every record.   We are hiring a Senior Applied Scientist to build these models from start to finish. You will contribute to designing the architecture, training at scale, and the optimization work that takes a model from training to running efficiently on production traffic. This optimization requires a deep understanding of the constraints imposed by both the software and the hardware, together with the applied mathematics to work within them: often it comes down to finding a mathematical reformulation that fits those constraints better, and that judgment can decide whether a model reaches production at all.   The work involves a number of open questions. How do you obtain most of the quality of a large model from one that is far smaller and cheap enough to run on the full stream? Where is it worth trading exactness for speed, and how do you reason about the error you accept? How do you make a small model's outputs clear enough that the detection engineers and analysts who rely on it can trust what it reports? If these are the problems you want to work on, we would like to hear from you.   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:   Design and build custom mid-size models for high-throughput stream processing, and train them at scale.   Optimize these models from start to finish, working across both the mathematics and the systems, often by finding mathematical reformulations that fit the hardware and software constraints better.   Build the training data pipelines the work depends on when they do not already exist, from the raw stream to a training-ready dataset.   Work with engineering to integrate models into production, with a clear focus on GPU utilization, latency, and cost per record on live traffic.   Plan the roadmap of model and system improvements, based on a solid understanding of the product and of what matters most to users.   Build an agentic layer on top of the models to analyze, validate, and act on their outputs.   Build lightweight interpretability tools that make model behavior easier to explain to the people who rely on it.   Maintain and monitor the models, services, and infrastructure your team owns, and take part in your team's on-call rotation.   Who You Are:   You have a BS/MS/PhD in Computer Science, Engineering, Machine Learning, Applied Mathematics, or a related scientific field, or equivalent experience.   You have hands-on experience training and fine-tuning models at scale, and deploying them into production systems with real throughput and cost constraints.   You have a working knowledge of how GPUs work, and a track record of making models run efficiently within real hardware constraints.   You have strong applied-mathematics fundamentals and reach for them naturally when designing and optimizing models.   You have a real passion for applied mathematics, software design, and implementation. This role sits at the intersection of the three, and it is a requirement for the position.   You care about code simplicity and performance, and you can build the data pipelines and the surrounding production code, in addition to the models themselves.   You can explain complex ideas and trade-offs clearly to engineers and product partners, and you let a solid understanding of the product guide what you build next.   Bonus: experience with efficient sequence architectures, model interpretability, or large-scale streaming systems.   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're passionate about technology and want to grow your skills, we encourage you to apply.  

Husky is what we call the distributed, petabyte-scale columnar event store at the heart of our Event Platform, which powers dozens of Datadog’s most popular products – Logs, RUM, APM, Cloud Network Monitoring, Netflow, and many more. Husky was built from the ground up at Datadog to store and query massive volumes of event data at low cost, with data fully queryable within seconds of arrival. As an Engineering Manager on Husky, you will lead one of a few closely collaborating teams that work directly on Husky’s internals. We own the full lifecycle of events stored by our Event Platform – whether it’s managing the ingestion of over 100 million events per second exactly-once, optimizing the persistence layer with lightning-fast compaction, tweaking our columnar format, timely deletion across hundreds of thousands of customer tables, or building the metadata service that enables hundreds of thousands of queries per second – you will be responsible for the growth and success of a team constantly meeting new scalability requirements driven by Datadog’s growing customer base and suite of products.   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 a team of software engineers ranging from new grads to senior engineers, focusing on career development, inclusivity, and high impact Be a technical leader of the team; while the role may not involve frequent hands on coding, you’ll be reviewing architecture decisions, RFCs, and pull requests and ensuring what the team ships is high quality Partner with product teams to evaluate use cases, ensure smooth implementation, and prioritize new platform capabilities.  Share on-call responsibilities with the rest of the team and ensure a culture of operational excellence Scale a petabyte-scale database to an exabyte-scale one   Who You Are:  A software engineer at heart with previous experience leading software engineering teams and a track record of delivering high-quality software products, preferably with some hands on experience with Java or Go and a background in distributed systems. Experienced with being on-call, leading incident responses, writing post mortems, and driving remediation efforts An excellent leader with strong interpersonal skills, with experience in career development and performance management. 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’re passionate about technology and want to grow your skills, we encourage you to apply.   

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 interpersonal skills, and the ability to build and lead high-performing teams Interested in working on an early stage project with many challenges to solve and a fast iteration cycle You build strong partnerships with cross-functional teams, including engineering, product, and science, and skillfully coordinate among multiple stakeholders You have a track record of delivering high-quality software on schedule and making decisions in ambiguous and fast-paced environments 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’re passionate about technology and want to grow your skills, we encourage you to apply.   

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 Engineering to integrate capabilities into Datadog's products and to harden prototypes into reliable services Contribute to research publications at top-tier conferences (e.g., NeurIPS, ICLR, ICML), and produce high-quality code, documentation, and open-source artifacts Who You Are:   You have depth in distributed computing, RL Infra, and ML systems for training and inference at scale; experience with Ray, Slurm, or similar frameworks is a plus You are proficient in Python, familiar with a systems language (e.g., Rust, C++, or Go), and comfortable with modern cloud and data infrastructure You have practical experience implementing and operating ML training and inference systems (e.g., PyTorch or JAX), including containerization, orchestration, and GPU acceleration You have practical experience with large-scale model training and fine-tuning, including frameworks like Megatron-LM, DeepSpeed, SkyRL, VeRL, or TorchTitan, and techniques such as SFT, RLVR, RLHF, and efficient inference (quantization, speculative decoding) You can explain design and performance trade-offs clearly to both technical and non-technical audiences You have experience supporting or contributing to research publications   Bonus Points (any of the following):   You have strong software engineering skills with experience in domains such as observability, SRE, or security You have experience bridging research prototypes and real-world product applications, especially with large foundation models, world models, or RL-trained agents You have a passion for pushing the boundaries of AI with a focus on customer impact and scalable deployment You have hands-on experience with GPU programming and optimization, including CUDA You have experience writing production data pipelines and applications You have experience building simulation or sandbox environments for agent training   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’re passionate about technology and want to grow your skills, we encourage you to apply.  

We’re looking for Software Engineering Interns to help build and scale the systems that power Datadog’s observability and security platform. Interns contribute directly to real-world engineering challenges across backend, frontend, infrastructure, data engineering, and developer tooling while working alongside experienced engineers and mentors. You’ll help design, build, and improve systems that process and analyze massive volumes of metrics, logs, and application data in real time. Whether you’re interested in distributed systems, Kubernetes, AI-powered products like Bits AI, or developer platform tooling, you’ll work on meaningful projects that deliver impact for customers at global scale.   At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.    What You’ll Do: Contribute to production systems that process and analyze large-scale observability and application data in real time Build and improve distributed systems across backend infrastructure, developer platforms, and cloud-native services Help identify and solve performance, reliability, and scalability challenges in critical services supporting Datadog’s growing customer base Own and deliver technical projects from design through deployment with guidance from experienced engineers and mentors Develop technical expertise through hands-on experience with technologies such as Kubernetes, distributed systems, and cloud-native infrastructure Collaborate with fellow interns, mentors, and engineers while building software that delivers impact at global scale   Who You Are: Pursuing a degree in Computer Science, Software Engineering, or a related technical field, or have equivalent practical experience Targeting a 2027 full-time start date Demonstrate strong computer science fundamentals, including data structures, algorithms, and software design Comfortable coding in one or more programming languages and excited to use AI-assisted tools to enhance software development and problem solving Have experience using AI coding tools or a strong interest in learning how to use them effectively while exploring how AI can improve engineering practices and products Available to complete a 6-month internship beginning in February, March, April, May, or June 2027 (we are unable to accommodate internships starting at any other time) Datadog values people from all walks of life. We know not everyone will meet all the above qualifications on day one. That’s okay. If you’re passionate about technology and want to grow your experience, we encourage you to apply.  

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. You have a strong systems mindset and enjoy solving complex infrastructure, scheduling, or capacity management challenges. You are comfortable working with operational data, capacity forecasting, or analytical approaches that inform engineering decisions. You have a proven track record of providing technical leadership across teams and influencing architecture without relying on direct management authority. Datadog values people from all walks of life. We know not everyone will meet all the above qualifications on day one. That’s okay. If you’re passionate about technology and want to grow your experience, we encourage you to apply.

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 the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.