System Verification Co Design Engineer Jobs

Datadog Sales Engineers help qualify and close opportunities with customers and partners. You will provide technical expertise through sales presentations, product demonstrations, and supporting technical evaluations (POCs). Sales Engineers have a voice with the product team to help prioritize features based on input from customers, competitors, and partners. Additionally, you will work with various teams to resolve customer concerns, escalate bug issues, and serve as an ambassador for our brand. If you want to join a friendly, passionate team with limitless potential, we’d love to meet you! 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: Partner with the sales team to articulate the overall Datadog value proposition, vision and strategy to customers Continually learn new technology to build competitive knowledge, technical skill, and credibility Deliver product and technical presentations with potential clients Have a direct line of communication with the product team to collaborate on feature requests Help clients onboard the product and assist when they run into roadblocks. Think creatively about a wide variety of technical challenges during the pre-sales life cycle Who You Are: Knowledgeable and experienced with DevOps monitoring or architecture tools. Comfortable and confident in delivering technical presentations/demos to either external customers or internal teams Able to think creatively about a wide variety of challenges. You're going to find new things every day Previously experienced in systems administrations: Windows or Linux Able to sit up to 4 hours, traveling to and from client sites Able to travel via auto, train or air up to 25% of the time Datadog values people from all walks of life. We understand not everyone

Datadog Sales Engineers help qualify and close opportunities with customers and partners. You will provide technical expertise through sales presentations, product demonstrations, and supporting technical evaluations (POCs). Sales Engineers have a voice with the product team to help prioritize features based on input from customers, competitors, and partners. Additionally, you will work with various teams to resolve customer concerns, escalate bug issues, and serve as an ambassador for our brand. If you want to join a friendly, passionate team with limitless potential, we’d love to meet you! 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: Partner with the sales team to articulate the overall Datadog value proposition, vision and strategy to customers Continually learn new technology to build competitive knowledge, technical skill, and credibility Deliver product and technical presentations with potential clients Have a direct line of communication with the product team to collaborate on feature requests Help clients onboard the product and assist when they run into roadblocks. Think creatively about a wide variety of technical challenges during the pre-sales life cycle Who You Are: Knowledgeable and experienced with DevOps monitoring or architecture tools. Comfortable and confident in delivering technical presentations/demos to either external customers or internal teams Able to think creatively about a wide variety of challenges. You're going to find new things every day Previously experienced in systems administrations: Windows or Linux Able to sit up to 4 hours, traveling to and from client sites Able to travel via auto, train or air up to 25% of the time Datadog values people from all walks of life. We understand not everyone

Datadog’s Revenue Operations & Finance team continues to expand as we work continuously to improve and solve complex business problems. The Sales Revenue team supports Datadog’s rapid growth by collaborating with teams across the organization, providing commercial, operational, and analytical support to ensure that Datadog's business and Sales organization continues to grow as rapidly and efficiently as possible. In this role, you will gain hands-on experience managing commission processes at scale while collaborating cross-functionally with Finance, Sales, Strategy, and Operations. This is an excellent opportunity for anyone seeking high visibility, meaningful ownership, and a clear path for growth within a fast-paced SaaS environment. We are looking for a Sales Revenue Analyst to join us in Boston, MA to support our team in managing global sales team compensation calculations and new business revenue recognition. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the monthly sales commission process across multiple sales segments, ensuring accuracy, timeliness, and operational excellence Improve day-to-day operations by identifying process gaps, fixing inefficiencies, and building practical tracking for new initiatives as the business grows Analyze compensation results to identify trends, surface risks, and provide actionable insights to leadership Review deal structures and financial terms to ensure alignment with compensation policies and revenue recognition requirements Partner cross-functionally with Finance, Sales, Systems and Strategy to support compensation plan execution and business initiatives Maintain and optimize compensation systems, reporting and dashboarding by leveraging tools such as Salesforce and CaptivateIQ to ele

Datadog’s Cloud Observability group is one of the core data retrieval and processing groups powering our foundational product, Infrastructure Monitoring. The group’s scope includes integration with all major hyperscalers (AWS, Azure, GCP, OCI), as well as both regional and GPU-specific cloud providers. As Director, you will own engineering for all clouds, generating more than 10 million metric points per second, managing ~40 engineers through a team of Engineering Managers. You’ll partner with Senior Directors and product leadership to shape the roadmap, not just execute against it, managing the growth of one of Datadog’s foundational teams. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You'll Do: Own engineering for all of Cloud Observability Manage ~40 engineers through a layer of Engineering Managers; this is a manager-of-managers role Shape the roadmap alongside product leadership rather than simply executing against it — push back on, iterate on, and help author the strategy for your area Drive AI adoption across the engineering org, from tooling and workflows to product features and team practices Navigate cross-team dependencies across the Agent, Telemetry Onboarding, Integrations, Action Platform, and Infrastructure Monitoring. Build and retain engineering talent in NYC, Boston, and Paris, mentor Engineering Managers toward Director readiness, and participate in the on-call rotation Who You Are: You have directly managed Engineering Managers, not just individual contributors You have deep experience with one or more cloud providers, ideally with experience operating large-scale systems in the cloud. You have a solid understanding of cloud economics, as well as how to balance performance and cos

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

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

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

MongoDB is seeking a Software Engineer 3 to join the Documentation Platform Engineering Team. The Documentation Platform delivers 60M page views a year and is critical to our users’ understanding of MongoDB products.It is also increasingly the context engine that helps AI tools understand, surface, and recommend MongoDB correctly. You will contribute to the evolution of our documentation platform by building and improving internal infrastructure, integrations, and applications that support our documentation and learning experience. This role can be based out of one of our offices in Canada or the USA, or remotely in Canada or the USA. Our ideal candidate Hands-on experience and understanding of Git, TypeScript, React, Next.js, CI/CD, MDX and other markup languages Experience with MongoDB (or a strong track record of working with other databases) Has worked on complex, in-production web applications Deep understanding of TypeScript or JavaScript, preferably TypeScript Can write, discuss, and review code in a collaborative way Understands how to make resilient, scalable, and maintainable software Has 2+ years of professional experience building and maintaining production software systems At MongoDB, you will Contribute to the development and enhancement of the MongoDB Documentation Platform Explore ways to improve documentation accessibility, discoverability, and user engagement Develop features that enhance the user experience for documentation consumers and contributors Contribute to and occasionally lead small-to-medium scoped features and platform improvements, collaborating with partner teams as needed Analyze user

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. 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

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

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

Join the Vector Search team and help build a cutting-edge vector database on top of MongoDB. Our team is responsible for the syntax and implementation of MongoDB's $vectorSearch aggregation, which enables approximate nearest neighbor queries over high-dimensional vectors. We are a small team with a large and rapidly growing customer base, providing engineers an opportunity to make a highly-visible, broad impact. When scaling search to billions of vectors, performance is paramount. We're looking for engineers who enjoy solving complex and open-ended problems that directly impact users' performance. This role is based in San Francisco, CA with a hybrid work model. You would get to: Implement new features within MongoDB's $search and $vectorSearch aggregation operators Work cross-functionally with Product teams to define new query and index syntax Identify and address performance bottlenecks in filter queries and nearest neighbor search Have the opportunity to lead projects and own subsystems Perform code reviews with peers, review technical designs, and mentor junior developers Ideally you will be: 3+ years of experience working on large-scale backend systems Experience writing high-performance applications in Java or another JVM language A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback Passionate about optimization, code quality, and problem solving Bonus: experienced with Apache Lucene, vector databases, or high-throughput web services Success Measures In 3 months you'll have a solid high-level understanding of what our team does and how we operate You'll have contributed to the development of an existing project and completed several small improvements or bug fixes In 6 months you'll be reviewing code and project designs, and be an active participant in team meetings In 12 months you'll have a thorough understanding of the systems our team owns and have led a small project. You'll have

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