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Join the MongoDB Server Query Optimization team, and help us build a world-class distributed open-source query optimizer. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, through parsing, optimization and plan selection. We have a presence across the US and Europe including New York, Dublin, Seattle, Palo Alto, and Chicago. We support office-based and remote work and align projects with convenient work hours for each time zone. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. The team is endeavoring to systematically rewrite every major component of our optimization and execution systems. We need your help to design and build the heart of a distributed, flexible schema, document database. ​​This role can be based out of our US offices or remotely in the North America region. Candidate Profile 10+ years of experience in data management systems, distributed systems, or large-scale backend engineering Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or similar field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases written in C++ or another systems programming language. You'll need to trace down defects, estimate work complexity, and design evolution and integration strategies as we rewrite different components of the system A strong foundation in core database internals is essential. While direct experience in query optimization is a massive bonus, it is not a prerequisite. We are also excited to meet candidates with strong backgrounds in compilers, language transpilers, or distributed storage systems Position Expectations Innovate in the area of flexible schema d

Join the MongoDB Server Query Execution team, and help us build a world-class distributed open-source database. Our team plays a crucial role in the performance and efficiency of MongoDB's data processing. We are responsible for building and improving the core execution engine that powers all queries, taking a logical query plan produced by the optimizer and turning it into reality. This includes developing the physical operators for data retrieval and manipulation, improving the runtime for complex analytical and transactional workloads, and owning critical components such as our new execution engine. In addition to the core server, we support the query execution needs of other major products like Atlas Streams, Atlas Search and Vector Search, and mongosync, making our work vital to the entire MongoDB ecosystem. You will be joining a globally distributed team with a significant presence in both North America and Europe. While this role is based in the NAMER region, you will regularly collaborate closely with colleagues across different time zones. We support both office-based work in our North America hubs like New York, as well as remote work. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. To meet the ever-increasing data demands of modern applications, we are actively evolving our query system; this includes strategically re-architecting and improving key components of our query execution engine. We need your help to design and build the core of a distributed, flexible schema document database. This role can be based out of one of our North America offices, such as NYC or Palo Alto, or remotely across North America. Candidate Profile 10+ years of hands-on, professional experience in query engine development or database internals Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or

The Code Gen team is tasked with building AI-powered code transformation tools that transform rigid, legacy applications that suffer from poor scalability and high operating costs into modern, microservices-based architectures that are built on top of MongoDB. Join our team and be at the forefront of innovation and creativity. We are looking for a Staff Engineer with domain expertise and years of experience in modernizing legacy applications that are based on traditional database systems. A significant advantage is profound prior experience in leveraging AI, particularly LLMs and GenAI capabilities, to enable reliable, self-driving automation of the code transformation, iterative build, and test processes. In this role, you will be instrumental in initiating technical strategies and ideas, lead the Code Gen team in designing, building, and optimizing our code transformation workflow and tools. You will work on critical components that ensure the scalability, efficiency, and reliability of our services. 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, build and test. This role will be based remotely in North America. A strong candidate for this position will have Extensive experience (8+ years) in software development and operations, with a proven track record of delivering high performance, correctness, and architectural excellence in fast-paced environments Experience using Relational Databases such as Oracle, MySQL, Microsoft SQL Server or PostgreSQL Experience with tools and methodologies for code analysis, refactoring, and automated testing Experience in designing and implementing complex software systems, collaborating effectively with engineers of all experience levels to achieve high reliability and performance Practical knowledge of integrating GenAI into large-scale, complex systems, including a clear unde

As a TPM for SRE, you will partner with SRE leaders and engineers to scale the platform that underpins all of MongoDB’s cloud products. You will drive program execution, strengthen production reliability practices, and coordinate cross-functional efforts across US and EMEA teams. Success in this role means smoother launches, clearer roadmaps, stronger reliability metrics and an SRE organization that's better-equipped to deliver predictability at scale. This role can be based out of our Dublin or Cork office or remotely in Ireland. What You'll Do Drive Program Planning & Execution – Define program scope, milestones, and success criteria with SRE engineers and leaders. Manage dependencies across platform teams, keep work clearly tracked in Jira, and deliver on time Strengthen Production Reliability – Lead change management and launch readiness programs. Partner with SREs and product teams to define and operationalize SLOs/SLIs, and use incident data, metrics, and capacity signals to drive prioritization and continuous improvement Lead Cross-Functional Coordination – Align SRE with Security, Compliance, Cloud platform, and other engineering teams. Coordinate cross-team incident response, ensure clear follow-through, and build trust as the go-to driver of complex, multi-team efforts Build Scalable Systems & Processes – Design lightweight frameworks and communication patterns that help SRE deliver reliably at scale. Work yourself out of the "hero" role by leaving teams better-equipped to execute independently Requirements 8+ years in technical program management, engineering management, or a comparable technical role partnering with software engineering teams Proven track record leading large-scale, cross-team platform initiatives through ambiguity and change Strong knowledge of production change management, software development lifecycle, and reliability metrics (SLOs, SLIs) Skilled at shaping roadmaps and managing dependencies Able to query and interpret

The Code Gen team is tasked with building AI-powered code transformation tools that transform rigid, legacy applications that suffer from poor scalability and high operating costs into modern, microservices-based architectures that are built on top of MongoDB. Join our team and be at the forefront of innovation and creativity. We are looking for a Staff Engineer with domain expertise and years of experience in modernizing legacy applications that are based on traditional database systems. A significant advantage is profound prior experience in leveraging AI, particularly LLMs and GenAI capabilities, to enable reliable, self-driving automation of the code transformation, iterative build, and test processes. In this role, you will be instrumental in initiating technical strategies and ideas, lead the Code Gen team in designing, building, and optimizing our code transformation workflow and tools. You will work on critical components that ensure the scalability, efficiency, and reliability of our services. 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, build and test. This role will be based remotely in North America. A strong candidate for this position will have Extensive experience (8+ years) in software development and operations, with a proven track record of delivering high performance, correctness, and architectural excellence in fast-paced environments Experience using Relational Databases such as Oracle, MySQL, Microsoft SQL Server or PostgreSQL Experience with tools and methodologies for code analysis, refactoring, and automated testing Experience in designing and implementing complex software systems, collaborating effectively with engineers of all experience levels to achieve high reliability and performance Practical knowledge of integrating GenAI into large-scale, complex systems, including a clear unde

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

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

Datadog is looking for a data-driven Associate Growth Marketing Manager to own the day-to-day execution, strategy, and optimization of our paid LinkedIn campaigns. In this role, you’ll be responsible for scaling LinkedIn ads that drive measurable results across global markets, with a strong focus on efficiency. This is an exciting opportunity for someone who combines analytical rigor with creative instincts, thrives in a performance-driven environment, and wants to deepen their expertise in paid media within a high-growth B2B company. 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: Manage campaign setup, budget allocation, and pacing, making data-informed decisions to drive high-quality, efficient leads and strong downstream performance Own campaign performance reporting and analysis Collaborate cross-functionally to promote products, webinars, events, and content across regions on LinkedIn and other digital channels (e.g., Reddit, Meta) Continuously test new audiences, bid strategies, messaging, creative, and landing pages to increase learning velocity and performance over time Who You Are: 2+ years of hands-on, in-platform experience managing LinkedIn Ads 3+ years working in marketing, ideally in a B2B or high-growth tech environment Comfortable manipulating and analyzing large datasets in Excel/Sheets, identifying trends, and translating insights into clear recommendations Experience with A/B testing, landing page optimization, and creative iteration Strong written and presentation skills, with the ability to clearly explain analyses and recommendations to stakeholders via PowerPoint/Slides Curious, proactive, and motivated by driving results Datadog values people from all walks of life. We understand not everyone will meet all the above qualificatio

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

Join the MongoDB Server Query team, and help us build a world-class distributed open source query engine. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, from parsing to optimization to plan selection and finally execution. This also includes our geospatial search and update subsystems. Our global team is growing fast. In North America, we have a presence across the US and Canada including New York, West Coast, Toronto. In Europe, we have a presence in Dublin, Germany, France, Netherlands, UK, Bulgaria, Spain and Italy currently. We support office-based and remote work and align projects with convenient work hours for each time-zone. We have tons of interesting problems to solve with direct impact on users for transactional, time-series and analytical workloads. We need your help to design and build the heart of a distributed, flexible schema, document database. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. Candidate Profile 3+ years of experience in data intensive environments Hands-on experience building industrial-strength software Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases B.Sc in Computer Science or similar field, or equivalent practical experience Experience in C++ and in developing database systems is a plus Interest in the theory and practice of database query engines. Hands-on experience or M.Sc./Ph.D in the domain is a plus Position Expectations Understand and improve current functionality of the MongoDB query engine Identify, design, implement, test, and support new features related to query performance and robustness, query language enhancements, diagnostics for query performance problems, and integration with other products and tools Work with other engineers to

About Voyage AI Team at MongoDB Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Position Overview We are seeking a Staff Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. This role can be based out of our Palo Alto office, or remotely in the United States. Responsibilities Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers Innovate in next-generation information retrieval and LLM agent paradigm Collaborate closely with other research scientists and research engineers as well as peers across the organization Qualifications PhD degree in Computer Science or related field A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues Strong background in machine learning, deep learning, and natural language processing Experience building complex neural networks for language and visual understanding Capable of conducting rigorous empirical studies to validate theoretical results Excellent leadership, problem-solving, and communication ski

As a TPM for SRE, you will partner with SRE leaders and engineers to scale the platform that underpins all of MongoDB’s cloud products. You will drive program execution, strengthen production reliability practices, and coordinate cross-functional efforts across US and EMEA teams. Success in this role means smoother launches, clearer roadmaps, stronger reliability metrics and an SRE organization that's better-equipped to deliver predictability at scale. This role can be based remotely on the East Coast What You'll Do Drive Program Planning & Execution – Define program scope, milestones, and success criteria with SRE engineers and leaders. Manage dependencies across platform teams, keep work clearly tracked in Jira, and deliver on time Strengthen Production Reliability – Lead change management and launch readiness programs. Partner with SREs and product teams to define and operationalize SLOs/SLIs, and use incident data, metrics, and capacity signals to drive prioritization and continuous improvement Lead Cross-Functional Coordination – Align SRE with Security, Compliance, Cloud platform, and other engineering teams. Coordinate cross-team incident response, ensure clear follow-through, and build trust as the go-to driver of complex, multi-team efforts Build Scalable Systems & Processes – Design lightweight frameworks and communication patterns that help SRE deliver reliably at scale. Work yourself out of the "hero" role by leaving teams better-equipped to execute independently Requirements 8+ years in technical program management, engineering management, or a comparable technical role partnering with software engineering teams Proven track record leading large-scale, cross-team platform initiatives through ambiguity and change Strong knowledge of production change management, software development lifecycle, and reliability metrics (SLOs, SLIs) Skilled at shaping roadmaps and managing dependencies Able to query and interpret metrics, logs, or other data s

MongoDB is seeking a Staff Software Engineer to join the Atlas Clusters Organization. The organization is responsible for building MongoDB Atlas, our database as a service offering and fastest growing product. Atlas allows users to deploy fault-tolerant, secure, globally distributed MongoDB clusters in just minutes. This includes developing software to interface with the three major cloud providers (AWS, Azure, and GCP) in order to bring security, durability, availability, and performance to all deployments of MongoDB. This engineer will also work on our Atlas Data Federation & Archiving product. Atlas Data Federation & Archiving allows customers to move data from hot to cold storage and run federated queries over that data. We are forming a new Atlas Clusters team in the Dublin area. We are looking to speak to candidates who are based in Dublin and would like a hybrid or in-office working model. What you’ll do Build and design new features for MongoDB Atlas and Atlas Data Federation & Archiving Contribute to and lead complex technical projects Work with stakeholders throughout MongoDB to build our roadmap and product offerings Work with customers and support engineers to fix issues and become part of our on-call rotation Collaborate with team members to develop our codebase, best practices, and design principles Foster an inclusive and respectful work environment according to MongoDB's Core Values We’re looking for someone who Has at least 10+ years of professional software development experience Is skilled at writing large-scale, distributed backend systems in a compiled language (Go, Java, C#, etc) Has experience with at least one major cloud provider technology (AWS, Azure, GCP) Has led the launch of a new module and maintained it in production Is eager to solve tough problems Has excellent communication skills Is curious, collaborative, and motivated Success Measures In 3 months, you'll have shipped code into production and c

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 MongoDB Cloud Services Team is a diverse group of contributors working together to help our users manage MongoDB at global scale. The Cloud Team is responsible for MongoDB Atlas: our database as a service offering, and fastest growing product, which allows users to deploy fault-tolerant, globally distributed MongoDB clusters in just minutes. The Backup Team delivers essential infrastructure to help our customers in their hour of need - providing the ability to quickly restore a massive, distributed database to any point in time at the click of a button. The Backup Team’s mission is to make MongoDB backup more reliable, faster, and also cheaper. This team is responsible for the Backup Agent (Go), the extensive server-side infrastructure (Java) which manages 100s of TB of data and processes billions of operations per day, and the user interface (Javascript) that customers use to manage their backups. Common project themes are performance, scaling, and ease of use. We are looking to speak to candidates who are based in New York for our hybrid working model. We're looking for someone who is Skilled at writing large-scale, distributed backend systems in a compiled language (Java, C#, Go, etc.) Fond of chasing down tough problems in a distributed systems environment Cool under pressure - has wrangled production crises, and secretly finds this a little fun Experienced with Linux, and able to correlate application performance problems with underlying hardware limits Comfortable working across the stack of a modern web application Always striving to expand their knowledge Curious, collaborative and intellectually honest Responsibilities Work closely with product teams, considering the user’s perspective while helping the team achieve success Collaborate with team members over best practices and core concepts Hold yourself accountable to your actions, maintaining the balance between accomplishing goals with research & development Own our