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Datadog is seeking a strategic, visionary, and results-oriented Senior Director, Growth Marketing – Organic Growth (SEO/GEO/PLG) to lead our organic acquisition strategy across traditional search engines and emerging AI/LLM platforms. This leader will own the vision, strategy, and operating model responsible for driving measurable growth in organic traffic and inbound pipeline through content programs, off-page authority, and AI/LLM discoverability initiatives. In this role, you will lead a team of organic growth specialists, while partnering closely with Website Experience, Product Marketing, and Engineering teams. You will define Datadog's long-term organic growth strategy, establish investment priorities, and ensure the organization is positioned to win across an increasingly complex discovery ecosystem. 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 Datadog’s content-led SEO/GEO/PLG strategy, defining the topics, formats, and ecosystems that drive measurable growth in traffic and pipeline Lead, coach, and develop a high-performing team Identify and prioritize high-impact content opportunities across product areas and influence cross-functional teams to bring that content to life Map and optimize Datadog’s presence across the full ecosystem of LLM-ingested content (e.g., YouTube, Reddit, review sites) to improve AI-driven discoverability Design and execute a comprehensive off-page strategy, including link acquisition, digital PR, and authority-building initiatives Partner closely with the Website Experience team, who owns technical SEO, to ensure content is effectively surfaced, indexed, and performant Create and contribute to high-impact content (e.g., flagship pieces, new formats, or experimental channels), setting the standard for qualit

We are a team of engineers that translate our real-world experience to help our user communities solve problems. With a focus on AI-accelerated workflows and next-generation developer ecosystems, you will have the opportunity to meet fast-moving teams where they are, helping them lay strong engineering foundations and broadening your impact to the developer community at large. This is a unique opportunity to use both your engineering depth and authentic storytelling skills to shape how the next wave of builders approach software health, scalability, and observability. What You’ll Do: Help developers hone their craft in an AI-accelerated world by exploring how AI coding assistants and rapid-prototyping tools change software workflows, and guiding teams on how to balance rapid prototyping with established engineering practices around performance, code health, and system reliability. Build in public by creating authentic, peer-to-peer technical content, sharing your engineering insights directly where modern developers collaborate in person and online. Drive a constructive, bidirectional feedback loop between fast-moving developer communities and our internal teams, translating real-world developer experiences into actionable product insights to shape our roadmap while advocating for user needs from the inside. Design and ship high-quality open-source boilerplate templates, quickstarts, and tools that make integrating observability seamless across AI native workflows, next-gen platforms (Vercel, Supabase, etc.), and cloud providers (AWS, GCP, Azure). Who You Are: A builder with approximately 10+ years of software engineering experience, ideally having shipped applications from scratch or worked within an early-stage startup environment where you've worn multiple hats. An AI-fluent developer who natively leverages AI coding assistants and rapid-prototyping tools as a core part of your regular, day-to-day development workflow. Multi-stack familiar, comfortable writing an

The Legal team supports Datadog’s rapid growth by providing a wide range of legal services across a highly dynamic technology company, from driving new business via contracts and compliance efforts, to protecting Datadog’s offerings. Datadog’s Legal team collaborates with virtually every team across the organization, from engineering to product to marketing. Within Legal, the Commercial, Alliances & Procurement team focuses on all commercial engagements, channel and alliances agreements, procurement matters, and related legal topics across Datadog’s global footprint. We are a collaborative, people-first team that values acting as trusted advisors, communicating clearly, embedding inclusion, and holding ourselves accountable. This role offers the chance to play a critical part in the success of a rapidly growing and innovative SaaS company in APJ, with a particular focus on our India and South East Asia regions. You will lead complex negotiations with Indian and South East Asia customers and partners and serve as a trusted advisor to internal stakeholders with a strong focus on the India region as our business rapidly expands in that region. The position requires someone who can negotiate complex agreements with Indian customers, have deep expertise in navigating the legal regulatory landscape in India and South East Asia while also supporting broader APJ commercial activity. You will also have the opportunity to influence and refine Datadog’s contracting and compliance approach across these fast-evolving markets. The role involves close collaboration with cross-functional teams including Sales, Deal Desk, Procurement, and Privacy. You will be expected to provide strong, practical solutions that balance legal risk with business objectives. This position will also give you exposure to cutting-edge SaaS technology areas such as privacy, security, and AI, allowing you to stay at the forefront of the industry. At Datadog, we place value in our office culture -

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection , error outliers and faulty deployment analysis . As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. 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: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performance You are excited to work on

Come join the Server Ingress Security team, where we are rearchitecting MongoDB Server’s ingress networking to make MongoDB clusters even more secure. This new team is building the Atlas Network Protection layer, a set of performant, security-critical services that harden MongoDB's pre-authentication attack surface and provides the ability to respond rapidly to emergent threats. We are looking for talented Staff Engineers to join the team and be founding members, where you will play a crucial role in our multi-year roadmap. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a key technical leader on a collaborative team that applies security and systems engineering fundamentals to protect a popular database at scale, join us! We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. Candidate Profile 10+ years of experience building production-quality systems software with a large user base, robust design structure, and rigorous code quality Experience with large backend/compiled codebases and performance-sensitive software, preferably in Rust Bonus points for experience working hands-on in security-sensitive or networking-adjacent domains Strong systems fundamentals, including multi-threaded programming and performance profiling. Bonus points for: Understanding of network protocols, TLS, and connection lifecycle management. Familiarity with security concepts such as attack surface reduction, input validation, memory safety, and defense-in-depth architectures. Excellent verbal and written technical communication skills for communicating to a wide variety of audiences ranging from junior engineers to executive stakeholder Strong mentorship skills, and excitement about leveling up your peers and teammates through coaching, feedback, and enablement Strong time management skills and the ability to realistically assess project complexity B.Sc. in Computer Science or a related

The Storage Layer Services team is currently re-architecting the MongoDB Cloud Storage Layer. This is a relatively new team in MongoDB that sits at the heart of the next generation MongoDB Cloud Storage Architecture, and the team is working to build performant multi-tenant distributed storage services both to enhance our existing MongoDB cloud storage architecture and to power more of our customers' use cases more efficiently. Engineering at MongoDB is globally distributed, with a mix of folks being fully remote, hybrid, or in-office. We have a small but growing team that calls Sydney home, and we are looking for a Staff Engineer to join the team working closely with other teams in Sydney and North America. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to work on a collaborative team that applies great engineering fundamentals to deliver core features of a popular database, join us! Let’s change what’s possible for application developers, system architects, and database operators. We are looking to speak to candidates who are based in Sydney for our hybrid working model. You’re an ideal candidate if: You have 10+ years of experience in programming, debugging, and performance tuning highly concurrent and/or distributed systems. Especially if you have worked in a systems language (C, C++, Rust, etc) for a number of those years You have a track record as an effective technical leader. You love helping teams be successful at solving vaguely defined problems in iterative and measurable ways. You put the customer first, and don’t hesitate to cross team boundaries in search of the right solution You have a solid grasp of related systems fundamentals, such as cache management, log-based recovery, transactions or performance profiling You’re comfortable reasoning about highly concurrent, asynchronous services — backpressure, tail latency, and the failure modes of replicated state machines You’ve worked on large, highly availabl

MongoDB is bolstering its hiring, focusing on creating tools that guide customers in transitioning their applications from relational databases to MongoDB. As businesses evolve their application development frameworks, they're increasingly drawn to the versatility of the document model. The Relational Migrator team, already instrumental in this area, aids developers in making the shift from relational databases to MongoDB. Now, they're broadening their toolkit and are keen on refining code using a mix of AI and traditional text processing. MongoDB is seeking a Software Engineer with solid software engineering skills and a machine learning background. Joining this team, you'll be pivotal in a product engineering group dedicated to helping users navigate code conversion challenges with AI's support. This role will be based out of North America in the PST and MST zones only. The ideal candidate for this role will have 2+ years of professional software development experience in Java or another programming language Experience with generative AI and specifically LLMs is highly desirable Experience with text processing engines such as ANTLR is highly desirable Strong understanding of software engineering, system design, data engineering and/or cloud architecture Have experience with compiler design, code parsing or related areas Familiarity with concepts like abstract syntax trees (AST), lexical analysis, and syntax analysis Curiosity, a positive attitude, and a drive to continue learning Actively engages in emerging trends and research relevant to product features Excellent verbal and written communication skills Position Expectations Collaborate with stakeholders to define and implement a code modernisation strategy, ensuring that transformed code aligns with modern software practices while preserving original functionality Develop and maintain a robust code parser to accurately interpret legacy code structures, converting them into a standardised format like an abstract

MongoDB is building a world-class team in North America to create tooling that helps customers modernize their applications and migrate their data from legacy relational databases to MongoDB in real-time. As companies modernise legacy workloads and data ecosystems, they are increasingly drawn to the flexibility and scalability of the document model. The tools developed by the Code Generation and Data Migration team are critical in this journey, helping customers with schema modeling, code generation, initial data loads, and continuous data synchronization. We're looking for a Software Engineer with a strong background in computer science fundamentals, systems design, experience in the Java ecosystem, streaming systems, and data-intensive applications to join our engineering team. In this role, you will be instrumental in designing, building, and optimizing the underlying data structures, algorithms, and database interactions that power our generative AI platform, code generation and migration tools. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation and building a sophisticated data migration suite using a modern technology stack, which includes Java, Spring Boot, Kafka, Debezium, and React.You will work on critical components that ensure the scalability, efficiency, and reliability of our services, collaborating closely with AI researchers, product management and other engineers to design and implement cutting-edge products that solve complex customer challenges. This role will be based out of Washington, Oregon, or California. The ideal candidate for this role will have 2+ years of engineering experience in backend systems, distributed systems, or core platform development Experience in one or several of Java, Rust, C/C++, and/or Python, with a strong understanding of systems-level programming, memory ma

We are seeking a Staff Site Reliability Engineer to join our growing Gurugram Products & Technology team to provide technical direction, shape architecture, and build key operational foundations of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Staff Site Reliability Engineer on this new team, you will be responsible for providing technical leadership for the operational foundations that enable deployment at scale of AI applications. You will own the reliability architecture of the platform as it expands across regions and cloud providers, and set the technical direction for how the platform is operated, including capacity planning, multi-cloud expansion, incident response, and SLO discipline. The platform's SRE team owns the operational foundations: the Kubernetes fleet, networking, observability and alerting, and tenant isolation. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Bengaluru for our hybrid working model. Position Expectations Own the reliability architecture of the platform across regions and cloud providers Collaborate with the teams building the platform, providing internal support and guidance on operability, capacity, and best practices Set operational standards for the team: on-call quality, incident response, SLO discipline Mentor and technically develop the SRE team Participate in a 24/7 on-call rotation to resolve issues involving platform infrastructure Qualifications 10+ years of experience working on software and operating distributed systems, with deep Kubernetes expertise, including designing or evolving multi-cluster platforms Proficiency in Python, Go, or a similar programming language Understand workload isolati

MongoDB is bolstering its hiring, focusing on creating tools that guide customers in transitioning their applications from relational databases to MongoDB. As businesses evolve their application development frameworks, they're increasingly drawn to the versatility of the document model. The Relational Migrator team, already instrumental in this area, aids developers in making the shift from relational databases to MongoDB. Now, they're broadening their toolkit and are keen on refining code using a mix of AI and traditional text processing. MongoDB is seeking a Software Engineer with solid software engineering skills and a machine learning background. Joining this team, you'll be pivotal in a product engineering group dedicated to helping users navigate code conversion challenges with AI's support. This role will be based out of North America in the PST and MST zones only. The ideal candidate for this role will have 2+ years of professional software development experience in Java or another programming language Experience with generative AI and specifically LLMs is highly desirable Experience with text processing engines such as ANTLR is highly desirable Strong understanding of software engineering, system design, data engineering and/or cloud architecture Have experience with compiler design, code parsing or related areas Familiarity with concepts like abstract syntax trees (AST), lexical analysis, and syntax analysis Curiosity, a positive attitude, and a drive to continue learning Actively engages in emerging trends and research relevant to product features Excellent verbal and written communication skills Position Expectations Collaborate with stakeholders to define and implement a code modernisation strategy, ensuring that transformed code aligns with modern software practices while preserving original functionality Develop and maintain a robust code parser to accurately interpret legacy code structures, converting them into a standardised format like an abstract

We are looking to speak to candidates who are based in Gurugram for our hybrid working model. About the Role We are looking for a Staff Integration Engineer (Workato & API Integration) to join our GTMTech team. This strategic role will lead the design, implementation, and governance of enterprise-grade integrations that power our core business processes across GTM systems, with a primary focus on Workato-based integrations and modern API management patterns. You will own the architecture for critical integration domains such as Quote-to-Cash and other high-impact GTMTech programs, ensuring our integration landscape is scalable, secure, observable, and aligned with best practices for event-driven and API-first designs. You will partner with engineering, architecture, security, and business stakeholders to define standards, mentor other integration engineers, and drive continuous improvement in how we connect systems and data. The GTMTech team is focused on high-impact, large-scale technology programs, such as Quote-to-Cash. Our mission is to enhance company efficiency, boost profitability, and enable data-driven decision-making by streamlining systems, optimizing processes, and minimizing manual, low-value work through automation and AI. Key Responsibilities Lead the end-to-end architecture, design, and implementation of Workato-based integrations and APIs across GTM systems (e.g., Salesforce, NetSuite, HRIS, Google Workspace) with a focus on scalability, reliability, and security Define and evolve integration standards, patterns, and best practices, including canonical integration patterns, error-handling strategies, observability, and operational runbooks Design and review complex, event-driven integration workflows leveraging technologies such as Kafka or equivalent messaging platforms, ensuring robust handling of topics, producers/consumers, durability, and retry mechanisms Drive API-first and MCP-native design for GTM integrations, leveraging RESTful APIs al

We are seeking a Staff Engineer to join our growing Gurugram Products & Technology team to provide technical direction, direct architecture, and implement core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Staff Engineer on this new team, you will be responsible for providing technical leadership to teams developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Work closely with research, product management, product engineering, product design, peers as well as other teams within the company to define the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 8+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer science and maint

Staff Forward Deployed Engineers (FDE) sit at the intersection of enterprise customer environments and a fast-moving internal product. They are senior technical leaders who own ambiguous, high-impact problems that span customer engagements, product direction, and engineering execution. They are accountable not only for getting customers to production, but for using what is learned in the field to shape reusable product capabilities, technical strategy, and delivery quality across multiple teams. This role is best suited for engineers who want to combine hands-on technical depth with broad influence: defining or changing strategy when customer reality reveals a gap, guiding technical decisions across teams, and translating field insight into durable product and engineering improvements. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Responsibilities Customer and business impact Own the most complex customer engagements and technical workstreams, especially where the problem, solution, or path to production is ambiguous Build deep understanding of customer architecture, business goals, constraints, and definition of success, and use that understanding to shape the technical approach rather than only execute within a predefined one Act as a trusted technical counterpart to customer’s engineering leaders, internal product and engineering leaders, and executive stakeholders when navigating complex tradeoffs, risks, and priorities Technical leadership and execution Lead architectural design for customer-facing solutions and platform capabilities within the FDE domain, balancing hands-on implementation with technical decision-making across multiple teams Take ambiguous, high-level problems and turn them into clear technical direction, implementation plans, milestones, and ownership boundaries that enable execution at quality and speed Continue to write and review production-quality code, troubleshoot complex failures, and set

Staff Forward Deployed Engineers (FDE) sit at the intersection of enterprise customer environments and a fast-moving internal product. They are senior technical leaders who own ambiguous, high-impact problems that span customer engagements, product direction, and engineering execution. They are accountable not only for getting customers to production, but for using what is learned in the field to shape reusable product capabilities, technical strategy, and delivery quality across multiple teams. This role is best suited for engineers who want to combine hands-on technical depth with broad influence: defining or changing strategy when customer reality reveals a gap, guiding technical decisions across teams, and translating field insight into durable product and engineering improvements. We are looking to speak to candidates who are based in New York City, NY for our hybrid working model. Responsibilities Customer and business impact Own the most complex customer engagements and technical workstreams, especially where the problem, solution, or path to production is ambiguous Build deep understanding of customer architecture, business goals, constraints, and definition of success, and use that understanding to shape the technical approach rather than only execute within a predefined one Act as a trusted technical counterpart to customer’s engineering leaders, internal product and engineering leaders, and executive stakeholders when navigating complex tradeoffs, risks, and priorities Technical leadership and execution Lead architectural design for customer-facing solutions and platform capabilities within the FDE domain, balancing hands-on implementation with technical decision-making across multiple t

About the Role We are seeking a Staff Enterprise Architect, Data to lead the strategy, design, and modernization of our enterprise data landscape. This role operates at the intersection of data architecture, engineering, and AI enablement, defining solutions to integrate our Data Lake and Data Warehouse across multi-cloud platforms. Over the next 12-18 months, you will enable self-service data access and natural language query capabilities for business users. You will architect Master Data Management and data lineage frameworks ensuring AI models operate on high-quality, governed data. You will also evaluate and implement AI-powered tools to automate data quality monitoring and enhance data security. We're looking to speak with candidates based in the San Francisco Bay Area for our hybrid working model. Key Responsibilities Data Strategy & Roadmap Design semantic layer architecture standardizing business metrics enterprise-wide. Define governance guardrails ensuring natural language queries access validated master data sources Develop Master Data strategy for Customer and Product domains (phases 1-2), Finance and People to follow. Define golden record requirements, stewardship models, and system-of-record hierarchy. Partner with business owners on master data governance Define cross-cloud data integration strategy and reference architecture. Specify patterns (federation, replication, abstraction layer) balancing performance, cost, and data freshness. Document trade-offs and recommend implementations for batch and near-real-time use cases Develop 12-24 month data architecture roadmaps for Finance, Sales, Product, and People. Identify capability gaps and recommend technology investments with business value and effort estimates Systems Design & Solution Leadership Evaluate AI-powered data observability platforms for quality monitoring, pipeline failure prediction, and data classification. Define requirements, lead vendor POCs, and establish integration patterns