Cloud Operations Engineer Jobs

As the Engineering Manager for Commercial Audit, you will lead a high-performing team responsible for scaling Datadog’s security and compliance posture through automation, tooling, and engineering excellence. Our GRC (Governance, Risk, and Compliance) function is a critical partner to the broader Security and Engineering organizations, ensuring that Datadog not only meets rigorous global regulatory standards but does so in a way that is efficient, scalable, and integrated into our cloud-native infrastructure. You will manage a team of engineers and analysts who are transitioning to a GRC engineering direction to treat compliance as a software problem, leveraging AI, custom tooling, CI/CD pipelines, and cloud-native services to turn complex regulatory requirements into actionable, automated controls. You will lead the strategy, roadmap, and execution of Datadog’s Commercial Audit initiatives. This is a high-impact leadership role where you will grow a team of engineers and analysts responsible for directly maintaining our compliance programs and related audits (e.g., SOC2, PCI, HIPAA, ISO) while looking to improve efficiency and effectiveness through platforms and tooling. You will act as a bridge between technical engineering, legal, and compliance, enabling the organization to move fast while maintaining a secure and compliant environment. You will champion a culture of "compliance-as-code," identifying opportunities to automate evidence collection, streamline control testing, and reduce manual toil for both your team and our partner engineering teams. 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 strategy, roadmap, and execution of Datadog’s commercial security compliance efforts, shifting from manual audit processes to automated, scalable

The data management software market is transforming how organisations build and run applications. MongoDB is the leading developer data platform and the first database provider to IPO in more than 20 years. Join us at the forefront of data and application development. MongoDB Technical Services Engineers combine deep technical expertise with exceptional problem-solving and customer-service skills. You’ll advise customers and resolve complex challenges across MongoDB Core, drivers, Atlas, Cloud Manager, cloud platforms, and infrastructure. We’re looking for candidates based in Dublin to join our vibrant office and collaborative in-office team. This is a five-day role with one of the following schedules: Tuesday–Saturday, Sunday–Thursday, or a five-day pattern covering both Saturday and Sunday. Under our hybrid model, employees on weekend schedules are expected to work from the office two days per week. Cool things you’ll do You’ll help customers troubleshoot complex issues and run critical MongoDB workloads with confidence. You’ll: Solve customer challenges across architecture, performance, recovery, and security Lead investigations from diagnosis to resolution, providing clear, actionable guidance Partner with Product Management and Engineering to advocate for customers and improve MongoDB Build tools, documentation, and training while mentoring peers and raising technical excellence What you need We value curiosity, adaptability, strong technical foundations, and a genuine desire to help customers. You should bring many of the following: 5–6 years of experience in technical support, systems engineering, database administration, SRE, or a related field Experience running complex, mission-critical production database systems Strong Linux and systems engineering skills, including performance, memory, I/O, storage, networking, security, clustering, and troubleshooting A solid understanding of networking concepts and protocols, including DNS, TCP/IP, and SSL/TLS Ability

MongoDB is seeking an Engineering Manager to join the Atlas 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. The Atlas Data Federation & Archiving team is an engineering team responsible for the Atlas capabilities that allow customers to move data from hot to cold storage and run federated queries over that data. The team builds Atlas Data Federation, a distributed query engine that lets users query data across Atlas Clusters and cloud object storage through a unified service. The team also builds Atlas Online Archive which allows customers to move data from Atlas Clusters into fully managed cloud object storage while preserving a seamless query experience across hot and cold datasets. We are forming a new Atlas Data Federation & Archiving team in the Dublin area. The Engineering Manager who fills this position will be pivotal in growing that team. We are looking to speak to candidates who are based in Cork and would like a hybrid or in-office working model. What you’ll do Lead a team of motivated individual contributors who are eager to learn and grow Contribute to the code, design, and architecture of the systems your team develops 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 6 years of professi

About Datadog: Datadog is a best-in-class SaaS business, delivering a rare combination of growth, profitability, and stock market appreciation. Built by engineers, for engineers, our monitoring and security platform is used by organizations of all sizes across a wide range of industries to enable digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stack. We’re dedicated to creating, developing, and supporting our product and customers, allowing for seamless collaboration and problem-solving among Dev, Ops, and Security teams globally. Come join the team for an exciting opportunity to learn from top-level leaders and colleagues and grow alongside the company as we rapidly expand. The Team: Our sales team works with a best-of-breed product that solves real problems for our customers. Sellers follow a well-defined methodology that helps them identify the customer's unique needs and clearly convey the value of the Datadog product. Whether you're looking to learn from the best or be the best, the Datadog sales team is dedicated to furthering personal development and team success. The Opportunity: Datadog is the monitoring and analytics platform for developers, IT teams and business users in the cloud age. We're scaling our Inside Sales team to help IT and Technology leaders recognize Datadog’s impact in their digital transformation and migration to the cloud. This is an opportunity to bring a proven product, loved by thousands of customers, to a multi-billion dollar market. You Will: Focus 100% on net new logo acquisition Manage the full sales cycle Run and partner with Sales Engineers on demos Use tools such as Sales Navigator and ZoomInfo Strategically prospect into CTOs, Engineering/IT Leaders, & technical end users You Are: Focused on hunting and closing net new logos A top performer with a history of success Bold on the phones, and creative in your emails Able to strategic

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 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 Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork and a great sense of humor to achieve exceptional results for our customers. We are looking to speak to candidates who are based in Mexico City for our hybrid working model. Cool things you’ll do MongoDB is on a mission to change the way people think about databases. Along the way, our customers encounter questions and issues about how our approach to databases works for their use case. In Technical Services, it's our job to help these people. You'll be working alongside our largest customers, solving their complex issues - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on standard methodologies in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - working with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. In addition, you will also be responsible for mentoring and ramping new team members and taking initiatives in building knowledge of new product lines within the MongoDB ecosystem. What you need We consider all candidates with an eye for those who are self taught, insatiably curious, and multi-faceted. It’s important for candidates to check off these boxes: Systems engineering experience, including Linux

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

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

As Engineering Manager for Threat Detection, you will lead a high-performing team that powers Datadog's detection program. Threat Detection is the organization responsible for keeping Datadog ahead of an evolving threat environment: closing coverage gaps faster, raising the bar on signal quality, and shipping detections that hold up under the scale and complexity of cloud-native infrastructure. Your team will combine direct detection expertise, platform engineering, and applied AI to ship detections at a pace and scale traditional rule-writing alone cannot match. Examples of what your team will work on include detection-authoring agents, the detection platform that powers every rule in production, coverage analysis, alert triage and response automation, and the evaluation infrastructure that holds these systems to a high bar of fidelity. Detection authorship is a shared responsibility across the organization, and your team will contribute both by building the systems that scale our authoring capacity and by writing detections directly when their domain expertise is the right tool. You will partner closely with our Security Incident & Response Team (SIRT), Cyber Threat Intelligence (CTI), AI Engineering teams, and Datadog's broader Security organization. This is a high-impact leadership role: you will grow a team of security and software engineers responsible for building and executing our detection and AI strategy. 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 strategy, roadmap, and execution of Datadog Security's shift to AI-accelerated detection and response. Drive development of high-fidelity detections as a shared responsibility across the organization, ensuring your team's systems and direct contributions raise the bar on coverage and

MongoDB is seeking an Engineering Manager to join the Atlas 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. The Atlas Data Federation & Archiving team is an engineering team responsible for the Atlas capabilities that allow customers to move data from hot to cold storage and run federated queries over that data. The team builds Atlas Data Federation, a distributed query engine that lets users query data across Atlas Clusters and cloud object storage through a unified service. The team also builds Atlas Online Archive which allows customers to move data from Atlas Clusters into fully managed cloud object storage while preserving a seamless query experience across hot and cold datasets. We are forming a new Atlas Data Federation & Archiving team in the Dublin area. The Engineering Manager who fills this position will be pivotal in growing that team. 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 Lead a team of motivated individual contributors who are eager to learn and grow Contribute to the code, design, and architecture of the systems your team develops 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 6 years of profes

MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhere—on premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, it’s no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications. Atlas Search is a multi-cloud service that allows users to execute complex full text and vector search queries using the MongoDB Query Language . Our users are free to focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team builds and maintains the instances and supporting infrastructure powering Atlas Search. This platform deploys and monitors search deployments, providing a highly scalable yet observable system for customers and engineers. The Atlas Search product is quickly gaining traction with customers and we are shipping core infrastructure components that enable this growth. This role is based in San Francisco, CA with an in-office or hybrid work model. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software and automation in complex codebases Experience developing distributed systems and multithreaded applications Familiarity with public cloud platforms, distributed infrastructure, and metric-based development Experience with at least one modern statically typed program

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

Role Overview Own the end-to-end technology strategy and roadmap for the Partner, Customer success, Professional Services and Customer Support organizations, translating business objectives into scalable, AI-native platforms. Lead a small team of Product Managers while staying hands-on across solutioning, architecture, and delivery. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Key Responsibilities Partner Technology Own the Partner Center technology roadmap spanning cloud provider integrations, partner attribution & telemetry, and incentive/MDF management Drive build-vs-buy decisions for the Partner platform in direct partnership with Partner leadership Deliver solutions that support the full partner lifecycle: onboarding, co-sell, information sharing, support, progress tracking, and program management across Resellers, Technology Partners, ISVs, and Cloud Marketplaces Align partner technology with Sales, Partner Ops, and Partner Specialist workflows Customer Success Technology Own the Customer Success technology stack supporting CSMs across the full customer lifecycle: onboarding, adoption, expansion, and renewal Partner with Customer Success leadership to translate business objectives into scalable tooling and automation Enable CSM productivity through health score visibility, account intelligence, and proactive risk alerting Ensure tight integration between Customer Success platforms and Sales, Support, Billing, and Product systems Drive adoption of AI-assisted workflows for CSMs including next-best-action recommendations, sentiment signals, and churn risk indicators Customer Support Technology Own the Customer Support technology stack to enable customer support team with right tooling, including AI/agentic infrastructure, ETL/data pipelines, Workforce Management, and customer engagement tooling (chat, voice, workflow automation) Partner with Technical Support, Customer Success, and Professional Services to al

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