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The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. 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: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r

As a Senior Security Engineer focused on Datadog’s Cloud SIEM product, you will help shape the future of security operations by transforming real-world security expertise into scalable detection, investigation, and response capabilities. You will develop high-impact threat detection content, improve AI-assisted security workflows, and help defenders identify and respond to threats across cloud-native and enterprise environments. Working closely with Product, Engineering, and Security Research teams, you will influence the evolution of Datadog Security products while advancing detection coverage across emerging technologies and attack surfaces. This role offers the opportunity to contribute to open source initiatives, publish security research, and help define the next generation of agentic security operations capabilities. 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: Research attacker techniques, defensive strategies, and emerging threats, translating findings into scalable security capabilities that protect customers at cloud scale. Design and improve AI-powered investigation, threat hunting, and response workflows that support Datadog’s agentic SOC capabilities. Own the lifecycle of threat detections and automated security workflows, from research and design through deployment, measurement, and continuous improvement. Develop high-fidelity detection content across cloud platforms, SaaS applications, identity systems, endpoints, networks, and other modern attack surfaces. Partner with Product, Engineering, Security Research, and customers to influence roadmap decisions and improve security outcomes across the platform. Mentor security engineers and drive improvements through automation, tooling, rapid prototyping, and data-driven optimization. Who Yo

As a Senior Security Engineer focused on Datadog’s Cloud SIEM product, you will help shape the future of security operations by transforming real-world security expertise into scalable detection, investigation, and response capabilities. You will develop high-impact threat detection content, improve AI-assisted security workflows, and help defenders identify and respond to threats across cloud-native and enterprise environments. Working closely with Product, Engineering, and Security Research teams, you will influence the evolution of Datadog Security products while advancing detection coverage across emerging technologies and attack surfaces. This role offers the opportunity to contribute to open source initiatives, publish security research, and help define the next generation of agentic security operations capabilities. 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: Research attacker techniques, defensive strategies, and emerging threats, translating findings into scalable security capabilities that protect customers at cloud scale. Design and improve AI-powered investigation, threat hunting, and response workflows that support Datadog’s agentic SOC capabilities. Own the lifecycle of threat detections and automated security workflows, from research and design through deployment, measurement, and continuous improvement. Develop high-fidelity detection content across cloud platforms, SaaS applications, identity systems, endpoints, networks, and other modern attack surfaces. Partner with Product, Engineering, Security Research, and customers to influence roadmap decisions and improve security outcomes across the platform. Mentor security engineers and drive improvements through automation, tooling, rapid prototyping, and data-driven optimization. Who Yo

You will have the opportunity to shape, mold, and impact how fast we grow, the way we’re viewed, and the candidate experience. We are looking to hire a Recruiter who will be responsible for finding the best talent; you will be the face of recruiting at Datadog! You will be the first point of contact for new candidates in the hiring process, playing a critical role in identifying great candidates, telling the Datadog story and ultimately turning great candidates into great employees. 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: Find qualified talent for our open roles via sourcing, job posts, referrals, and agencies Screen candidates to ensure their qualifications match the open roles Collaborate with leadership to design or streamline interview processes Ensure follow up and closure for all interviewed candidates Negotiate compensation with qualified candidates Enhance our recruitment process through training interview teams Leverage Greenhouse to track candidate progress through funnel, resurface existing talent, and keep consistently clean data for reporting Ensure candidates have an excellent interview experience - regardless of outcome Who You Are: Experienced in full-lifecycle recruiting, with 2-5 years either in-house or in a staffing agency environment A sourcing master in your ability to identify where top talent lives Autonomous with a demonstrated ability to work independently and simultaneously on multiple positions Exceptional at selling value proposition, negotiating and closing great candidates Skilled at operating with a sense of urgency in all stages of the recruiting cycle Able to successfully navigate an ever-changing process Datadog values people from all walks of life. We

You will have the opportunity to shape, mold, and impact how fast we grow, the way we’re viewed, and the candidate experience. We are looking to hire a Recruiter who will be responsible for finding the best talent; you will be the face of recruiting at Datadog! You will be the first point of contact for new candidates in the hiring process, playing a critical role in identifying great candidates, telling the Datadog story and ultimately turning great candidates into great employees. 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: Find qualified talent for our open roles via sourcing, job posts, referrals, and agencies Screen candidates to ensure their qualifications match the open roles Collaborate with leadership to design or streamline interview processes Ensure follow up and closure for all interviewed candidates Negotiate compensation with qualified candidates Enhance our recruitment process through training interview teams Leverage Greenhouse to track candidate progress through funnel, resurface existing talent, and keep consistently clean data for reporting Ensure candidates have an excellent interview experience - regardless of outcome Who You Are: Experienced in full-lifecycle recruiting, with 2-5 years either in-house or in a staffing agency environment A sourcing master in your ability to identify where top talent lives Autonomous with a demonstrated ability to work independently and simultaneously on multiple positions Exceptional at selling value proposition, negotiating and closing great candidates Skilled at operating with a sense of urgency in all stages of the recruiting cycle Able to successfully navigate an ever-changing process Datadog values people from all walks of life. We

You will have the opportunity to shape, mold, and impact how fast we grow, the way we’re viewed, and the candidate experience. We are looking to hire a Recruiter who will be responsible for finding the best talent; you will be the face of recruiting at Datadog! You will be the first point of contact for new candidates in the hiring process, playing a critical role in identifying great candidates, telling the Datadog story and ultimately turning great candidates into great employees. 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: Find qualified talent for our open roles via sourcing, job posts, referrals, and agencies Screen candidates to ensure their qualifications match the open roles Collaborate with leadership to design or streamline interview processes Ensure follow up and closure for all interviewed candidates Negotiate compensation with qualified candidates Enhance our recruitment process through training interview teams Leverage Greenhouse to track candidate progress through funnel, resurface existing talent, and keep consistently clean data for reporting Ensure candidates have an excellent interview experience - regardless of outcome Who You Are: Experienced in full-lifecycle recruiting, with 2-5 years either in-house or in a staffing agency environment A sourcing master in your ability to identify where top talent lives Autonomous with a demonstrated ability to work independently and simultaneously on multiple positions Exceptional at selling value proposition, negotiating and closing great candidates Skilled at operating with a sense of urgency in all stages of the recruiting cycle Able to successfully navigate an ever-changing process Datadog values people from all walks of life. We

The Internal Product Analytics (IPA) team is the analytics backbone of Datadog's Product organization. With over thirty products on a single platform, IPA gives PMs and leadership the data, tooling, platform, and analysis they need to make good decisions. The team owns the recurring analytical work the Product org runs on and builds the AI-first workflows that make that analysis faster and more consistent across the org. As Manager of the Internal Product Analytics team, you will directly manage a team of data analysts, partner closely with the PMs your team serves, and partner with the associated platform engineering teams. You will set the direction for how the team delivers analysis, builds AI-first tooling, and partners across functions. This is a role for someone who works well across teams, turning complex data and open questions into clear, trusted answers that PMs and leadership can act on. What You'll Do: Guide and grow the Internal Product Analytics team. Manage, coach, and develop a team of data analysts. Set priorities, hold a high bar for quality, and make sure the team's output is trusted across the Product org. Partner directly with the PM org. Work side by side with the PMs your team serves to frame the questions that matter, shape the analysis, and make sure the answers reach them in a form they can act on. Own the recurring analytics the PM org runs on. Business reviews, feature request analysis, usage and adoption tracking, and pricing analysis. Make this work consistent, repeatable, and fast so PMs get answers when they need them. Build AI-first analytics. Design and ship AI-powered workflows and agents that do the heavy lifting of analysis, from data querying to synthesis to reporting. Set the standard for how the team uses AI so analysis scales without simply adding headcount. Partner across functions. Work with Finance, Data Platform, Engineering, and Revenue teams to align on definitions, source the right data, and turn raw signals into decis

Join the Vector Search team and help build a cutting-edge vector database on top of MongoDB. Our team is responsible for the syntax and implementation of MongoDB's $vectorSearch aggregation, which enables approximate nearest neighbor queries over high-dimensional vectors. We are a small team with a large and rapidly growing customer base, providing engineers an opportunity to make a highly-visible, broad impact. When scaling search to billions of vectors, performance is paramount. We're looking for engineers who enjoy solving complex and open-ended problems that directly impact users' performance. This role is based in San Francisco, CA with a hybrid work model. You would get to: Implement new features within MongoDB's $search and $vectorSearch aggregation operators Work cross-functionally with Product teams to define new query and index syntax Identify and address performance bottlenecks in filter queries and nearest neighbor search Have the opportunity to lead projects and own subsystems Perform code reviews with peers, review technical designs, and mentor junior developers Ideally you will be: 3+ years of experience working on large-scale backend systems Experience writing high-performance applications in Java or another JVM language A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback Passionate about optimization, code quality, and problem solving Bonus: experienced with Apache Lucene, vector databases, or high-throughput web services Success Measures In 3 months you'll have a solid high-level understanding of what our team does and how we operate You'll have contributed to the development of an existing project and completed several small improvements or bug fixes In 6 months you'll be reviewing code and project designs, and be an active participant in team meetings In 12 months you'll have a thorough understanding of the systems our team owns and have led a small project. You'll have

Our Database Experience (DBX) Team A great MongoDB experience starts with great tools. The Database Experience team builds the libraries and tools that developers use day-to-day working with MongoDB. Our mission is to increase developer adoption, satisfaction and retention by providing a reliable, enjoyable interface for developers and other end-users. Our senior engineers are typically specialists in a particular programming language, but are capable of contributing to projects in other languages as well. For this role, we're looking for someone who will enjoy designing, writing, and supporting open source libraries for the Python ecosystem developers that use MongoDB. This is an opportunity to make a major impact at MongoDB as Python is one of the most popular runtimes for MongoDB users, and our driver has over 3 million daily pypi downloads. You might be right for this role if you... Have substantial experience writing high-quality software in Python Have extensive knowledge in Python tools and frameworks, scientific python and web development frameworks Have practical experience with AI/ML frameworks and technologies in Python, including large language models and agentic tools are a plus Have an interest in learning and staying up-to-date with Python ecosystem trends and best practices and incorporating them into your work Can make pragmatic design decisions, balancing tradeoffs such as usability, maintainability and delivery time Want to, or already do, participate in open source software development and communities, both online via e.g. GitHub and optionally through conferences and speaking engagements Communicate well, internally and externally, both verbally and in writing Enjoy collaborating with teammates, and mentoring junior engineers and interns Are self-motivated, organized, and have strong time management skills You'll be on the team responsible for... Developing and supporting the MongoDB Python drivers and subsidiary libraries ( PyMongo , Django Mon

The Infrastructure Engineering team is responsible for building and maintaining a self-service internal development platform that enables MongoDB engineering teams to reliably deploy and operate their own production services and products. We work with numerous engineering teams across the company to understand their infrastructure requirements and development workflows, develop broadly applicable self-service platform services and tooling, continuously monitor how platform services are being utilized, and look for ways to improve developer productivity through automation and education. We are big open source enthusiasts and use a number of open source tools in our stack (contributing upstream whenever possible). Some of the tools we use regularly include Go, AWS, Kubernetes, Crossplane, Terraform, Helm, Drone, Prometheus, and Grafana. However, technology is nothing without a stellar team of engineers that are focused on doing high quality work and working as a team to solve complex distributed computing and platform engineering problems. This is where you come in! We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Our ideal candidate Has built and operated large-scale distributed systems in cloud providers (AWS strongly preferred) Has a strong backend programming background. Fluency in Go is strongly preferred; deep experience with another compiled or strongly-typed backend language is acceptable Has experience working with AI coding agents and can demonstrate building high quality context to yield high quality outputs Has experience designing and implementing medium-to-large software projects, including driving design reviews and mentoring less-senior engineers Pragmatic, detail-oriented, self-motivated, and understands the benefits of collaboration Strong experience operating production Kubernetes clusters, not just deployed to it Has practical experience defining and operating against SLI/SLOs for services they owned Str

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in the US or can be based out of any of our US offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in Canada or can be based out of any of our Canada offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent to

AI frameworks like LangChain, LlamaIndex, and n8n are quickly becoming the default way developers build with AI — and MongoDB wants to be the data platform that shows up everywhere they build. As part of the AI Builders Experience (ABX) org, we're standing up a brand new engineering team in Gurugram to make that happen, and we're looking for Senior Software Engineers to be among its founding members. The team owns the connective layer between MongoDB and third-party AI frameworks, platforms, and tools — the integrations that let developers use MongoDB effectively with the AI stack they've already chosen. That means shipping into some of the fastest-moving open-source ecosystems in tech, working mostly in Python and TypeScript, and partnering with the Database Experience (DBX) org when an integration needs new driver, platform, or product capability underneath it. This is a self-sufficient team by design. You and your engineering manager will be based in Gurugram, and the group is set up to own its area end to end: to decide how integrations get built, tested, released, and maintained, without waiting on another time zone to unblock the day-to-day. You'll work closest with the engineers sitting next to you, pairing on hard problems, reviewing each other's code, and dividing up a broad portfolio, while collaborating with product, partners, field teams, and open source maintainers as the work requires. You'll integrate with fast-moving, often unproven technologies, make pragmatic calls in the face of ambiguity, and own high-visibility projects with minimal guidance. Priorities can shift week to week based on framework changes, customer demand, and partner needs, so we're looking for product-minded engineers who thrive on autonomy and take pride in shipping. Much of your work will happen in public: sending pull requests to upstream repositories, working through external maintainer review cycles, and representing MongoDB in developer communities. MongoDB engineering team

Our Database Experience (DBX) Team A great MongoDB experience starts with great tools. The Database Experience team builds the libraries and tools that developers use day-to-day working with MongoDB. Our mission is to increase developer adoption, satisfaction and retention by providing a reliable, enjoyable interface for developers and other end-users. Our senior engineers are typically specialists in a particular programming language, but are capable of contributing to projects in other languages as well. For this role, we're looking for someone who will enjoy designing, writing, and supporting open source libraries for the Python ecosystem developers that use MongoDB. This is an opportunity to make a major impact at MongoDB as Python is one of the most popular runtimes for MongoDB users, and our driver has over 3 million daily pypi downloads. You might be right for this role if you... Have substantial experience writing high-quality software in Python Have extensive knowledge in Python tools and frameworks, scientific python and web development frameworks Have practical experience with AI/ML frameworks and technologies in Python, including large language models and agentic tools are a plus Have an interest in learning and staying up-to-date with Python ecosystem trends and best practices and incorporating them into your work Can make pragmatic design decisions, balancing tradeoffs such as usability, maintainability and delivery time Want to, or already do, participate in open source software development and communities, both online via e.g. GitHub and optionally through conferences and speaking engagements Communicate well, internally and externally, both verbally and in writing Enjoy collaborating with teammates, and mentoring junior engineers and interns Are self-motivated, organized, and have strong time management skills You'll be on the team responsible for... Developing and supporting the MongoDB Python drivers and subsidiary libraries ( PyMongo , Django Mon

MongoDB’s Developer Productivity organization exists to help engineers build and deliver high-quality software through a highly effective software development process and a strong foundation of shared tools and services. We are looking for a Senior Director to lead our Pipeline team. This role is tasked with bringing together the major systems and experiences that power software delivery at MongoDB. The team’s mission is to provide a reliable, scalable, secure, and effective platform for ensuring fast software deployability, leveraging AI native approaches. We are open to in-office, flexible or remote hiring across Canada. The Team The Pipeline organization sits within Developer Productivity and is responsible for the systems, services, and user experiences that define MongoDB’s software delivery ecosystem. This is mission-critical infrastructure operating at substantial scale and supports a variety of software product delivery needs. Success in this role requires excellent product judgment for developer-facing experiences, strong systems and platform leadership, and the ability to align multiple teams around a cohesive strategy. Candidate Profile We’re looking for a senior engineering leader who can unify product-minded developer tooling with deep platform and operational excellence. The right candidate is passionate about developer productivity and has a track record of leading managers and teams through organizational growth, technical complexity, and cross-functional change. They should be comfortable owning a broad portfolio that spans developer experience, reliability and scale, release systems, telemetry, and operational health. They should also be able to work effectively with senior leaders and partners across engineering and product to set direction, allocate resources, and make trade-offs that balance near-term delivery with long-term platform function. The right candidate for this role will 12+ years of hands-on software engineering experience bui