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Data Semantics is Datadog’s authority on semantic knowledge, providing shared infrastructure that powers both Datadog’s product experiences and AI capabilities. As Datadog continues its investment in OpenTelemetry-native observability, semantic interoperability, and AI-powered workflows, this team sits at the center of some of the company’s most strategic platform initiatives. As a Staff Engineer, you will serve as a technical leader for the team, balancing stewardship of critical production systems with the exploration of new platform capabilities that improve how telemetry is modeled, understood, and consumed across Datadog. You will work closely with engineering and product partners to define standards, drive technical direction, and deliver solutions that scale across Datadog’s observability platform. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead the technical direction of the Data Semantics team while remaining deeply hands-on in design, implementation, and delivery. Build and scale semantic infrastructure that bridges OpenTelemetry, Datadog-native telemetry, cloud-provider telemetry, and customer-defined data models. Drive platform initiatives focused on schema evolution, telemetry standardization, data insights, and semantic interoperability across Datadog products. Partner with engineering and product teams across the platform to define standards, align stakeholders, and deliver high-leverage platform capabilities. Mentor engineers through design reviews, technical guidance, operational excellence, and long-term career development. Participate in on-call rotations and lead investigation and resolution efforts for complex production incidents affecting critical platform services. Who You Are: You have significant experience designing, opera

We’re looking for a Staff Product Designer to join the APM (Application Performance Monitoring) team. This team is focused on helping engineers agentically troubleshoot and optimize their applications. You'll learn the domain and proactively spot areas for improvement, getting stakeholder buy-in as needed. You'll own your design work end-to-end while helping shape broader product direction. You'll also hold a high bar for quality across the team and help other designers build support for their decisions. 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: Become a design leader within APM by proactively identifying opportunities and shaping the design strategy across multiple product areas and workflows. Partner closely with PMs and Engineers to ship intuitive experiences, balancing user needs with platform scalability and engineering constraints. Conduct and synthesize qualitative and quantitative research to identify pain points, validate solutions, and guide roadmap decisions. Communicate design rationale clearly and persuasively across design, engineering, product, and executive stakeholders. Mentor and support other designers by providing feedback, sharing frameworks and workflows, and helping raise the overall design quality bar across the organization. Prototype in code to rapidly explore ideas and validate concepts. Contribute to production code using AI-assisted workflows to ensure execution matches design intent. Help the team adopt AI-enabled design workflows. Who You Are: You have 10+ years of experience in digital product design. Your portfolio demonstrates a strong track record of designing and shipping complex technical products. You use AI-assisted workflows to prototype and rapidly iterate. You have a track record of connecting

As a Staff Product Manager on Datadog's Observability Data Platform (ODP) , you will lead product management for a portfolio of foundational platform bets — work that changes the cost structure and capability of the platform itself, not the cost of any single feature. Among ODP’s portfolio of engineering work are efforts to bring the platform's unit cost down meaningfully each quarter, plus a slate of architectural bets aimed at order-of-magnitude cost reduction over the longer horizon. The work you'll lead reshapes how Datadog ingests, routes, and exposes telemetry value to customers — and is foundational to how every product team in Datadog's ecosystem will think about telemetry economics going forward. This role reports to the Group Product Manager of ODP. What You'll Do: Set product direction across foundational platform bets by defining problems and desired outcomes, partnering with engineering to determine slices of work that drive value in phases for users and the business. Collaborate on the long-term cost-and-value architecture of the platform — how value-aware telemetry, innovative data engines, and customer-facing cost stories fit together over multiple quarters. Develop and defend sizing and impact estimates for large, diffuse programs — credibly produce the analysis that engineering leadership and pricing partners need to make resourcing and prioritization calls. Anticipate and communicate market trends in telemetry economics and agentic observability and how they shape platform investment. Develop deep understanding of cost-to-serve by partnering with engineering on the unit economics of the data platform and bring that cost-profile understanding into collaborative discussions with product verticals about customer-facing trade-offs. Surface the customer-positive angles in cost work that engineering-led optimization tickets don't currently make visible. Deliver concise written and verbal communication to executive, engineering, and customer audien

As a Staff Engineer on the Data Platform Experience team, you'll help shape how Datadog engineering teams build, operate, and evolve products on the Observability Data Platform. You'll lead the design and delivery of shared platform capabilities that reduce developer friction, improve operational visibility, and enable engineering teams to move faster with confidence. This role combines deep distributed systems expertise with technical leadership across multiple teams, influencing platform strategy while remaining hands-on in the code. You'll have the opportunity to solve company-wide challenges spanning cost intelligence, operational tooling, platform health, and developer experience. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Lead strategic engineering initiatives that improve how product teams build, operate, and evolve services on the Observability Data Platform. Design and build scalable platform capabilities for cost intelligence, including cloud cost allocation, trend analysis, and optimization recommendations. Develop operational intelligence and self-service tooling that helps engineering teams understand platform health, troubleshoot incidents, and improve operational efficiency. Drive reusable platform services and developer workflows that increase engineering autonomy while reducing operational complexity across multiple products. Provide technical leadership across teams by influencing architecture, mentoring engineers, and raising engineering standards through hands-on technical contributions. Participate in the team's on-call rotation and continuously improve platform reliability, observability, and operational excellence. Who You Are: You have experience designing and building large-scale SaaS or cloud platforms with deep expertise i

We are seeking a highly skilled Staff IT Product Manager for Internal AI to drive the strategy, delivery, and adoption of AI-powered solutions across our enterprise IT landscape. This role will be pivotal in shaping how AI transforms our internal operations, from service delivery and knowledge management to automation and decision support. The ideal candidate has a proven track record of managing enterprise-scale AI/ML products, collaborating across IT and business functions, and delivering measurable impact. We are looking to speak to candidates who are based in San Francisco, CA or Palo Alto, CA for our hybrid working model. Key Responsibilities AI Product Strategy & Roadmap Define and execute the internal AI product strategy aligned with enterprise IT and business goals Own multiple product lines in the internal AI product space Prioritize high-value use cases across IT functions (helpdesk, infrastructure, security, applications, enterprise data) Balance quick wins (AI copilots) with longer-term bold initiatives (AI-driven automation and decision-making) Experience in implementing AI solutions for enterprises our size and scale. This should include enabling agentic platforms for organizations and bringing to the table the best practices, pitfalls and learnings from such experiences Product Management Execution Embrace the product mindset and own the lifecycle of AI products—from ideation, critical user journey definition, requirements gathering, vendor evaluation, prototyping, and implementation to scaling in production Define and manage product backlogs, roadmaps, and success metrics Drive adoption and ensure AI solutions are delivering measurable outcomes (efficiency, cost savings, user experience) Stakeholder Engagement Partner with IT leaders (Applications, Infrastructure, Security, Service Desk) to identify pain points and AI opportunities Collaborate with business stakeholders to ensure alignment and secure sponsorship for AI initiatives Communica

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

The Data Engineering team is responsible for building ETL pipelines that populate the Internal Data Platform, which drives analytics that help the company run more efficiently. Our team builds highly performant and scalable processes that extract massive datasets and makes those datasets available for querying in an optimal way. We are looking to speak to candidates who are based in Gurgaon for our hybrid working model. What you’ll do Guide the Data Engineering team on building highly performance ETL pipelines using Spark and other Big Data technologies Help design the architecture of our Internal Data Platform to support the implementation of a robust medallion architecture Provide thought leadership on ways to achieve infrastructure cost savings on Cloud hyperscalers Design and build AI agents that can help automate many of the common development and support tasks that the team performs Work with Security and Compliance teams to ensure that datasets have appropriate permissions and regulations in place Work with our Data Platform, and Governance sibling teams to make data scalable, consumable, and discoverable We’re looking for someone with 10+ years experience working on enterprise data lakes/warehouses 5+ years of Spark and Python experience 5+ years of direct hands-on experience working with AWS or GCP Thorough AI knowledge, particularly with codegen tools and agentic frameworks Hive, Iceberg, Glue, or other technologies that expose big data as tables Familiarity with different big data file types such as Parquet, Avro, and JSON Exposure to real-time or streaming data technologies is a plus Success Measures In 3 months, you'll have a thorough understanding of the architecture of MongoDB’s internal Data and AI ecosystem In 6 months, you'll have owned the delivery of a large project from start (scoping, design) to finish (delivery) In 12 months, you'll have designed new features, led development work, and become a go-to expert on parts of the system About MongoDB

MongoDB is hiring a Staff Product Marketing Manager to build and own our go-to-market narrative for the Public Sector vertical, with a focus on Federal Government and the broader public sector market. This is a foundational hire for MongoDB’s Industry Verticals product marketing function: you will define how MongoDB’s unified data platform, spanning cloud, on-premises, and hybrid database deployments with integrated, production-ready AI capabilities, shows up for government buyers. You’ll turn a major compliance milestone into a durable competitive differentiator: developing the positioning, messaging, and sales-ready content that helps government agencies, systems integrators, and cloud/public-sector resellers understand why MongoDB is the right data platform for mission-critical, regulated workloads. You do not need prior government or public-sector work experience to succeed in this role — you need to be an excellent product marketer who can get fluent in a new domain quickly and partner closely with the compliance, product, and sales experts who already are. This role can be based in one of our MongoDB hub offices in the U.S. or remotely in the U.S. What you’ll do Own positioning and messaging for MongoDB’s Public Sector go-to-market, leading the federal GTM and launch related activities Translate MongoDB’s data platform capabilities — document database, search, vector search, stream processing, and integrated AI — into mission-relevant outcomes and value propositions for government buyers and the systems integrators who serve them Partner with Compliance, Security, Industry Solutions and Product teams to accurately represent related certification requirements in external-facing content, staying current as MongoDB pursues additional authorizations (e.g., DoD Impact Levels) Build the public sector sales enablement toolkit: battlecards, pitch decks, discovery guides, ROI/value models, and competitive intelligence tailored to federal buying processes and procuremen

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. The Collections team is a newly formed team within MongoDB's Observability & Adoption Org focused on making telemetry onboarding and collection significantly easier across MongoDB. We own key parts of the observability collection stack, including onboarding experience, telemetry collection agents across the data and control planes, and ingestion services for metrics, logs, and traces that support both internal and customer observability in MongoDB, driving insights, recommendations, and alerting. Our mission is to reduce friction for teams implementing and iterating on Observability while partnering closely with development teams to instrument their services using shared best practices, helping define the conventions our telemetry should follow, and building collection and ingestion systems that are stable, performant, secure, well-documented, and self-service. We also work closely with the Data Pipeline and Storage & Query teams to help ensure MongoDB has a stable and performant observability stack end to end. This is an opportunity to join a team shaping how observability works across MongoDB and to have outsized impact on both the developer experience and the reliability of the platform underneath it. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Grafana, Sp

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. This is an opportunity to join a team that is responsible for all Observability systems that support metrics, metric visualization, logs, traces, and alerts for MongoDB. We are looking for engineers with high standards, and experience in setting direction and technical leadership for large engineering teams in designing and operating complex distributed systems, with strict SLO on security, durability, availability and performance. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Splunk, Flink, WarpStream/Kafka, Java, Golang Fluentbit. In addition to owning critical components of our observability infrastructure, as a Staff engineer on the team, you’ll also work closely with other SWE, Product and SRE teams to promote and implement best practices in instrumenting and monitoring their services. This is a highly collaborative role, and you will get to own some of the most relied upon internal infrastructure at Mongo. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a deeply technical leader on a collaborative team that applies low-level systems expertise to build the foundational infrastructure of a popular database, join us! Let’s build a faster, more reliable, and exceptionally observable database system together. W

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. The Collections team is a newly formed team within MongoDB's Observability & Adoption Org focused on making telemetry onboarding and collection significantly easier across MongoDB. We own key parts of the observability collection stack, including onboarding experience, telemetry collection agents across the data and control planes, and ingestion services for metrics, logs, and traces that support both internal and customer observability in MongoDB, driving insights, recommendations, and alerting. Our mission is to reduce friction for teams implementing and iterating on Observability while partnering closely with development teams to instrument their services using shared best practices, helping define the conventions our telemetry should follow, and building collection and ingestion systems that are stable, performant, secure, well-documented, and self-service. We also work closely with the Data Pipeline and Storage & Query teams to help ensure MongoDB has a stable and performant observability stack end to end. This is an opportunity to join a team shaping how observability works across MongoDB and to have outsized impact on both the developer experience and the reliability of the platform underneath it. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Grafana, Sp

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

The Role MongoDB is seeking a Staff Product Manager to lead strategic initiatives across Identity and Security. In this role, you will serve as the senior product leader shaping the next generation of authentication, authorization, and access control across MongoDB Atlas, the core database engine, and emerging developer platforms. You will lead the strategy for non-human identity—spanning workload identity federation, zero-trust passwordless access, Model Context Protocol (MCP) integrations, and autonomous AI agentic identity. You will partner closely with engineering, UX, product marketing, and enterprise customers to build identity experiences that are enterprise-grade, seamless for developers, and secure by default. Responsibilities Set and champion a multi-year product strategy across interrelated identity areas, aligning dependencies and investments to MongoDB’s broader objectives Identify cross-cutting customer and market opportunities, build business cases for investment, and bring a clear point of view to senior stakeholders Lead workload identity federation and programmatic access initiatives across cloud and enterprise identity environments Define secure authorization approaches for AI agents and MCP clients, including delegation, identity lifecycle, policy, and administrative controls Drive developer-first access management, ensuring security controls enhance rather than obstruct developer velocity Partner with engineering, design, GTM, and cross-functional leadership to validate enterprise requirements, prioritize initiatives, and measure feature adoption Stay ahead of evolving cloud security paradigms, emerging standards (e.g., SPIFFE/SPIRE, O4AA), and AI access patterns to guide executive decision-making Represent MongoDB’s security and identity vision at industry events, customer advisory boards, and executive briefings Demonstrate creativity, an innovative spirit, and a bias towards action Requirements 8+ years (or equivalent experience) in Pro

MongoDB’s Security Product Management team is seeking a Staff Product Manager to own security, compliance, and public sector product strategy within Atlas for Government (A4G). In this role, you will be a key member of the security product management team, helping make data security a market differentiator that enables MongoDB to win in enterprise and regulated industries. You will lead product strategy and execution for capabilities and programs that support federal compliance requirements and broader regulated-industry needs. You will work across Engineering, Compliance, Legal, Security, and Go-to-Market teams to translate complex regulatory and customer requirements into clear product investments, roadmaps, and outcomes. This role is suited for a candidate who can orchestrate multiple interlinked product areas, own cross-team product and architectural trade-offs, and align senior stakeholders around multi-year bets. You will be expected to identify opportunities and dependencies that cut across team boundaries, bring clarity to ambiguous problem spaces, and establish reusable ways of working that help MongoDB deliver secure, compliant platform capabilities for public sector and other regulated markets. You will partner closely with senior engineering and business leaders to evaluate trade-offs, sequence investments, and bring clarity to decisions that balance customer impact, execution risk, and long-term business value. This role can be based out of of our offices or remotely in the United States. The Federal Risk and Authorization Management Program (FedRAMP) is a US government-wide program that provides a standardized approach to security assessment, authorization, and continuous monitoring for cloud products and services. Our FedRAMP program requires that anyone who is accessing customer data or metadata inside the Authorization Boundary be a US Person on US Soil. Responsibilities Security and Compliance Product Strategy Own the public sector compliance roadm

The Role MongoDB is seeking a Staff Product Manager to lead strategic initiatives across Identity and Security. In this role, you will serve as the senior product leader shaping the next generation of authentication, authorization, and access control across MongoDB Atlas, the core database engine, and emerging developer platforms. You will lead the strategy for non-human identity—spanning workload identity federation, zero-trust passwordless access, Model Context Protocol (MCP) integrations, and autonomous AI agentic identity. You will partner closely with engineering, UX, product marketing, and enterprise customers to build identity experiences that are enterprise-grade, seamless for developers, and secure by default. Responsibilities Set and champion a multi-year product strategy across interrelated identity areas, aligning dependencies and investments to MongoDB’s broader objectives Identify cross-cutting customer and market opportunities, build business cases for investment, and bring a clear point of view to senior stakeholders Lead workload identity federation and programmatic access initiatives across cloud and enterprise identity environments Define secure authorization approaches for AI agents and MCP clients, including delegation, identity lifecycle, policy, and administrative controls Drive developer-first access management, ensuring security controls enhance rather than obstruct developer velocity Partner with engineering, design, GTM, and cross-functional leadership to validate enterprise requirements, prioritize initiatives, and measure feature adoption Stay ahead of evolving cloud security paradigms, emerging standards (e.g., SPIFFE/SPIRE, O4AA), and AI access patterns to guide executive decision-making Represent MongoDB’s security and identity vision at industry events, customer advisory boards, and executive briefings Demonstrate creativity, an innovative spirit, and a bias towards action Requirements 8+ years (or equivalent experience) in Pro