Security Software Development Engineer Jobs

The Documentation team creates engaging and informative technical content, particularly our public product documentation: Datadog Docs . This is an opportunity for a Documentation Manager to help us deliver high quality technical documentation and lead one of our growing documentation teams. Our team is hands-on with the technologies that Datadog monitors, and collaborates with technical and product teams to create technical documentation for our APIs, SDKs, developer and security tools, and community developed integrations — thousands of pages of content! This role is remote in North America. What You’ll Do: Manage 3-5 technical writer direct reports, overseeing their day-to-day, helping them make and manage effective content project plans, formally supporting their growth and development, and fostering an environment that encourages positive engagement and performance. Partner with our Product and Engineering teams to create and maintain public documentation for users, developers, and SREs, helping them succeed with Datadog products, features, SDKs, APIs, and developer tools. Experiment with the product, dig into source code, and interview subject matter experts to research technical details for documentation. Collaborate with our contributor community and greater Documentation team to develop and improve documentation standards and processes. Who You Are: You have 5-10 years experience researching and developing documentation for technical topics, like databases, APIs, cloud infrastructure, and performance and security monitoring. You have 2-5 years experience managing a small team of technical writers, coaching their performance, guiding their career journey, and breaking down complex projects into achievable plans. You have publicly available technical writing samples. You are comfortable reading at least two programming languages (e.g. Ruby, Python, Go, bash). You have written or managed documentation as code, and are familiar with modern infrastructure such a

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

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

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

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

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

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

MongoDB Technical Services Engineers use their outstanding problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Services Engineers in the Infrastructure team are skilled in automation, backup, performance, and security that underpins mission-critical deployments at scale. In addition engineers within the team have specialisations in advanced technology areas such as Search, Vector Search, auto-embedding, event-driven and agentic workloads. Our engineers combine their MongoDB expertise with passion, initiative, teamwork, and a great sense of humor to achieve exceptional results for our customers. The position will be based in our Sydney office. The standard work week post ramping will be Tuesday to Saturday, every week. Why MongoDB is a fantastic place to work and build your career Be a part of the company that’s reinventing the database, passionate about innovation and speed Enjoy a fun, inspiring culture that is engineering focused Work with exceptionally talented people around the globe Learn, contribute, and make an impact on the product and community Cool things you’ll do MongoDB, the developer data platform and AI platform of choice for modern applications, is on a mission to change the way people think about databases. As they build intelligent, data-driven experiences on our platform, our customers naturally encounter questions and challenges about how our approach to data and databases fits their specific use cases and architectural needs. In Technical Services, it’s our job to guide these people, helping them design, operate, and optimize their solutions so they can succeed with MongoDB. 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, wh

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

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

The IT SaaS Engineering Team plays a critical role in optimizing MongoDB sales processes, streamlining customer interactions, and maximizing the efficiency of our sales efforts. By leveraging Salesforce, the team ensures that business users have the tools, automation, security, and governance needed to effectively manage customer relationships, support operational processes, and drive business growth. With deep expertise in Salesforce development, platform governance, automation, and system operations, the team continuously enhances the CRM platform to meet evolving business needs. The team partners closely with stakeholders across Sales Operations, Revenue Operations, Security, Compliance, and Engineering to deliver scalable, secure, and reliable Salesforce solutions. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Role Overview We are looking for a highly capable Senior Salesforce Engineer to design, build, and maintain scalable CRM solutions that support MongoDB’s Sales organization. This role combines strong hands-on Salesforce development, solution design, cross-functional collaboration, and a modern engineering mindset to deliver reliable, maintainable, and high-quality solutions across the core Salesforce platform. What you’ll do Design, build, and maintain scalable Salesforce solutions across the core CRM platform, including custom development, automation, and integrations Partner with business stakeholders, program managers, and technical teams to understand requirements and translate them into secure, maintainable, and scalable technical solutions Own delivery across the full solution lifecycle, including design, development, testing, deployment, documentation, and production support Collaborate closely with globally distributed engineering teams to deliver reliable, secure, and well-governed solutions in an Agile environment Drive strong engineering practices across code quality, documentation, release managem

The IT SaaS Engineering Team plays a critical role in optimizing MongoDB sales processes, streamlining customer interactions, and maximizing the efficiency of our sales efforts. By leveraging Salesforce, the team ensures that business users have the tools, automation, security, and governance needed to effectively manage customer relationships, support operational processes, and drive business growth. With deep expertise in Salesforce development, platform governance, automation, and system operations, the team continuously enhances the CRM platform to meet evolving business needs. The team partners closely with stakeholders across Sales Operations, Revenue Operations, Security, Compliance, and Engineering to deliver scalable, secure, and reliable Salesforce solutions. We are looking to speak to candidates who are based in New York for our hybrid working model. Role Overview We are looking for a highly capable Senior Salesforce Engineer to design, build, and maintain scalable CRM solutions that support MongoDB’s Sales organization. This role combines strong hands-on Salesforce development, solution design, cross-functional collaboration, and a modern engineering mindset to deliver reliable, maintainable, and high-quality solutions across the core Salesforce platform. We are looking to speak to candidates who are based in New York City, NY for our hybrid working model. What you’ll do Design, build, and maintain scalable Salesforce solutions across the core CRM platform, including custom development, automation, and integrations Partner with business stakeholders, program managers, and technical teams to understand requirements and translate them into secure, maintainable, and scalable technical solutions Own delivery across the full solution lifecycle, including design, development, testing, deployment, documentation, and production support Collaborate closely with globally distributed engineering teams to deliver reliable, secure, and well-governed solutions in an A

We are looking to speak to candidates who are based in Gurugram for our hybrid working model. About MongoDB The database market is massive, and MongoDB is at the head of its disruption. The MongoDB community is transforming industries and empowering developers to build amazing applications that people use every day. We are the leading modern data platform and continue to innovate at scale to support our customers and internal teams with world-class systems and experiences. About Team IT SaaS Engineering Team plays a critical role in optimizing MongoDB sales processes, streamlining customer interactions, and maximizing the efficiency of our sales efforts. By leveraging Salesforce, the team ensures that business users have the tools, automation, security, and governance needed to effectively manage customer relationships, support operational processes, and drive business growth. With deep expertise in Salesforce administration, platform governance, automation, and system operations, the team continuously enhances the Salesforce CRM platform to meet evolving business needs. The team partners closely with stakeholders across Sales Operations, Revenue Operations, Security, Compliance, and Engineering to deliver scalable, secure, and reliable Salesforce solutions. What you’ll do We are looking for a Senior Salesforce Administrator to manage and enhance the Salesforce CRM system supporting MongoDB’s Sales organization. Effectively work both autonomously and collaboratively across Salesforce platform administration, configuration, release support, security, and audit-related activities. Work closely with Tech Leads, Program Managers, Developers, DevOps teams, and Business Stakeholders to understand requirements and deliver scalable declarative solutions. Contribute across multiple functions including platform administration, CI/CD participation, release support, access governance, security improvements, and audit readiness. Ensure appropriate controls, documentation, and go

The IT SaaS Engineering Team plays a critical role in optimizing MongoDB sales processes, streamlining customer interactions, and maximizing the efficiency of our sales efforts. By leveraging Salesforce, the team ensures that business users have the tools, automation, security, and governance needed to effectively manage customer relationships, support operational processes, and drive business growth. With deep expertise in Salesforce administration, platform governance, automation, and system operations, the team continuously enhances the Salesforce CRM platform to meet evolving business needs. The team partners closely with stakeholders across Sales Operations, Revenue Operations, Security, Compliance, and Engineering to deliver scalable, secure, and reliable Salesforce solutions. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. What you’ll do We are looking for a Senior Salesforce Administrator to manage and enhance the Salesforce CRM system supporting MongoDB’s Sales organization Effectively work both autonomously and collaboratively across Salesforce platform administration, configuration, release support, security, and audit-related activities Work closely with Tech Leads, Program Managers, Developers, DevOps teams, and Business Stakeholders to understand requirements and deliver scalable declarative solutions Contribute across multiple functions including platform administration, CI/CD participation, release support, access governance, security improvements, and audit readiness Ensure appropriate controls, documentation, and governance practices are followed to maintain a strong and effective control environment Responsibilities Administer, configure, and maintain the Salesforce platform, including users, roles, profiles, permission sets, sharing settings, page layouts, record types, and other core administrative functions Build and enhance Salesforce solutions using declarative tools such as Flows, Validation Rule