Systems Engineering Intern in Ireland

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Developer Productivity group is responsible for making Stripe’s developers happy and productive. We work on tools, processes, and code refactoring to accelerate Stripe engineering as Stripe scales. We’re looking for people with an interest in building the tools to improve the day to day experience of Engineers in Stripe. The ideal candidate will have a passion for solving developer experience problems, and a pragmatic ability to ship results iteratively—powered by a mix of technical expertise across some or all of: language processing tools; version control systems; build systems; and distributed systems engineering. You’ll be working on a mix of engineer-facing systems, CI infrastructure platforms, and big-data engineering. What you’ll do We have a ton of important work to do, which is why we’re hiring! Our active projects change all the time, but here are a few examples of recent projects so you can get an idea of the types of work we do: Build and manage systems to handle CI at massive scale—including batching, speculative stacking, merge-race inhibition, and more. Build and manage systems to handle our enormous CI test suite–identifying and managing flaky tests, assessing and reproducing flakiness, and optimizing for test effectiveness. Enhance our CI systems for reliability, including adaptive response to available capacity, resilience and self-recovery from outages, and highly-leveraged observability. Detect and isolate code breaka

The worldwide data management software market is massive, forecasted to grow from approximately $82 billion in 2023 to approximately $137 billion in 2027. At MongoDB, we are transforming industries and empowering developers to build amazing apps that people use every day. We are the leading developer data platform and the first database provider to IPO in over 20 years. Join our team and be at the forefront of innovation and creativity. We are looking for a Technical Services Engineer to join our team in Dublin for a dedicated Tuesday through Saturday shift. We are looking to speak to candidates who are based in Dublin for our hybrid working model. About the Team MongoDB Technical Services Engineers (TSEs) use their exceptional problem-solving and customer service skills, along with deep technical experience, to advise customers and solve complex MongoDB problems. TSEs are experts in the entire MongoDB ecosystem, including the database server, drivers, and services like Atlas and Cloud Manager. Our engineers combine MongoDB expertise with passion, initiative, and teamwork to achieve exceptional results. Cool Things You’ll Do Work alongside our largest customers and partners to solve complex issues involving architecture, performance, recovery, and security Serve as an expert resource on standard methodologies for running MongoDB at scale Act as an advocate for customer and partner needs by collaborating with product management and development teams Contribute to internal projects, such as the software development of support tools for performance, benchmarking, and diagnostics Mentor and ramp up new team members while building knowledge of new product lines within the MongoDB ecosystem Work with top ISV partners to ensure excellence for joint customers What You Need Solid hands-on experience with systems engineering, including Linux performance, memory management, I/O tuning, configuration, security, networking, and troubleshooting A strong understanding of net

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. The Escalation Manager is a critical role within Technical Services. As a member of our global Incident and Escalation Management team, they work internally with our Engineering, Services, Sales and Product Management teams, as well as externally with customers and partners, to coordinate and drive the resolution of critical technical issues and incidents. Transparency is key and is achieved by providing timely and accurate updates to senior management regarding active escalations, as well as important detail on the status of the customer account. Individuals in this role are highly organized, proactive and professional. You are one who excels in fast-paced environments and can assess business impact, mobilize cross-functional teams, and drive technical escalations with urgency and ownership. We are looking for someone who has a customer-focused mindset with excellent communication and expectation-setting abilities. You have a technical background in Support, Services, DevOps, Systems Engineering, or Database environments, and are experienced in incident response or crisis management. You will have strong negotiation and objection-handling skill

As Senior Data Scientist for Engineering Systems you will work independently alongside sharp, generous, and pragmatic engineers from Server Query, Atlas Clusters, and Release Quality, among other teams. Together, we tackle problems spanning resource scaling across the Atlas fleet, safe feature rollout to MongoDB clusters, automated incident response and query engine performance. Join the Platform Data Science team and help us research, prototype and ship machine learning features for MongoDB’s core server, query engine and Atlas, our database-as-a-service cloud offering. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. What You'll Do Partner with Server Query, Atlas Clusters, Release Quality and other engineers to embed algorithmic rigor and optimization into resource scaling, release-safety and monitoring systems across the fleet and inside query engine Deliver production-ready, thoroughly tested statistical and ML algorithms with well-identified limitations that deliver measurable business impact, not just an impressive-sounding methodology Own the full feedback loop: instrument model architecture with the metrics needed to track performance and create dashboards in collaboration with our stellar analytics team, collect feedback from users and metrics to diagnose issues or opportunities, and iterate accordingly Deliver thoughtful, kind code reviews to your peers and act as a core contributor to internal packages, tooling, and team processes that increase developer productivity Measures of Success In 3 months, you’re familiar with our workflow, have an elementary understanding of our product and what teams we work with. You have delivered small-to-medium improvements to our project portfolio In 6 months, you’ve delivered one feature you researched and prototyped from scratch and demonstrated its impact on business metrics of your choice In 12 months, you've established a track record of shipping ML-driven improveme

Cloud Operations Engineers are responsible for building internal tools and process automation. Day-to-day duties are creating and monitoring systems alert dashboards, reviewing critical event and system logs, accessing customer instances that underpin their production databases, and performing server administration duties including performance troubleshooting. Applicants must be critical thinkers who are quick to detect, resolve, or escalate issues that are sometimes broad in scope and difficult to trace. We are looking for a Lead with strong technical leadership experience as well as technical depth who is looking to collaborate closely with Cloud Operations Engineering Management in building and maintaining a high-performing team that delivers high quality outcomes while fostering psychological safety and professional growth. We are looking to speak to candidates who are based in Dublin for our hybrid working model. Core responsibilities Team leadership: partner with and assist COE Management with the tasks of providing ongoing technical feedback to engineers, support their growth and creating an inclusive team environment Execution and delivery: play a key role in guiding team members through project deliverables ensuring high quality outcomes while also assisting in meeting or resetting timelines when required Time management: between assisting team members with day to day tasks ranging from incident to project management Cross-functional collaboration: work closely with Product, Technical Services and R&D to surface team’s pain points and drive alignment with the goal of providing an excellent user experience to the end customer Coordinate with Lead counterparts within Cloud Operations as well as Technical Services to ensure our uptime guarantees to the MongoDB Atlas customer base Assist and collaborate with the team on scoping, designing, deploying and ongoing maintenance of systems that focus on reducing mean time to resolve customer incidents Detec

About the Team The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and engineering teams across OpenAI to support lawful data access requests and other critical legal workflows. Our work turns complex, high-stakes processes into auditable and dependable technical systems with clear human oversight and strong privacy and security controls. About the Role We’re looking for a full-stack Software Engineer to build the internal tools and data pipelines that power lawful data access request workflows and Legal Operations. You will work across product and data systems to make authorized retrieval and case handling accurate, efficient, and auditable. This role is well suited to someone who enjoys translating ambiguous operational requirements into durable systems, cares deeply about sensitive-data handling, and wants to improve both technical reliability and the day-to-day experience of the people operating these workflows. In this role, you will: Design, build, and operate backend systems and workflow tooling for the full lifecycle of lawful data access requests, from intake and scoping through authorized retrieval, review, preparation, and audit. Build reliable data pipelines and interfaces across products and data stores so authorized teams can locate and handle the right records accurately and reproducibly. Implement least-privilege access, approval gates, provenance, audit trails, data minimization, and safe failure modes for sensitive workflows. Partner with Legal and Legal Operations to translate legal and operational requirements into clear technical designs and intuitive operator experiences. Identify responsible automation opportunities that reduce repetitive work while preserving human review, judgment, and accountability. Own production systems through testing, observability, incident response, documentation, and continuous reliability improvements. Hel

About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The payments landscape is changing rapidly, with businesses and their customers relying on a growing mix of local payment methods, cards, wallets, bank payments, buy now, pay later, and digital currencies. Stripe’s Local Payment Methods (LPM) business is one of our fastest-growing payments businesses. LPM Foundations builds and operates the core platform that enables Stripe’s Local Payment Method teams—and their first- and third-party developers—to build, integrate, and run high-quality payment methods at scale. We turn complex product integrations into reusable, self-service platform capabilities so teams can launch new LPMs faster and reduce the long-term cost of operating them. This is a payments role with a platform and AI focus. We are building the foundations, interfaces, and workflows that let product and engineering teams use AI effectively to accelerate development, improve decisions, and scale reliable payments experiences globally. What you’ll do As an Engineering Manager, you will lead the LPM Foundations team at the center of Stripe’s long-term payments growth strategy. You will translate regional and strategic priorities into a focused platform roadmap, shape technical direction with your team, and drive execution across the systems behind critical payment flows. You will be deeply involved in engineering and design, while coaching, mentoring, and creating the conditions for an effective, inclusive team. Responsibilities Set the vision an

About the Team The Solutions Engineering team consists of trusted technical advisors who help organizations adopt OpenAI’s technology safely, effectively, and responsibly. We partner closely with customers, Sales, Product, Engineering, Research, and Security to translate frontier AI capabilities into practical workflows that create measurable impact. Cybersecurity is one of the most important areas where AI can help. As frontier models become increasingly capable of reasoning across code, logs, infrastructure, vulnerabilities, and security evidence, customers need expert guidance to evaluate and deploy these systems safely. Our Field Security Specialists help security leaders and practitioners apply OpenAI models, APIs, Codex, agentic workflows, and emerging cyber capabilities to real defensive challenges. About the Role We are looking for a Manager of Field Security Specialists to build and lead our customer-facing cyber solutions engineering function. This is a hands-on leadership role for someone who can develop an exceptional team while remaining close to the technology and our customers. You will establish the operating model for the function, raise the quality of specialist engagements, and personally support our most strategic and technically complex customer opportunities. You will work across CISO-level strategy, practitioner-level cybersecurity challenges, and hands-on solution design. Your team will help customers explore workflows including application security, secure software development, vulnerability management, threat modeling, cloud and identity security, SOC operations, detection engineering, incident response, and security validation. This is not an internal CISO or corporate incident-response role. It is a customer-facing leadership opportunity focused on helping defenders achieve safe, measurable outcomes with frontier AI. In this role, you will: Hire, coach, develop, and lead a high-performing team of Field Security Specialists. Establish the

We’re hiring a Senior Technical Product Marketing Manager to lead positioning, messaging, and product adoption across our AI and agentic context solutions. This is a high-impact role for a technical marketer who thinks and acts like a builder. Most AI systems don't fail because the model is bad—they fail because they lack a crucial, contextual foundation. MongoDB owns a piece of nearly every step in that chain. This role requires deep technical expertise across the context stack—including VoyageAI embedding and reranking models, MCP Server, and the coding agent ecosystem (Claude Code, Cursor, GitHub Copilot, Gemini CLI, Codex, etc.)—combined with product marketing instincts to deeply understand the market and translate technical depth into crisp, differentiated messaging for distinct user and buyer personas. The ideal candidate has experience building and shipping AI-enabled products and using developer tools in their day-to-day workflows. Individuals with prior experience in technical sales, developer relations, or software development are encouraged to apply. The ideal candidate is a voracious consumer of AI research and pays close attention to shifting patterns in how software and AI applications are built and consumed. This individual is confident in communicating with technical practitioners and non-technical decision makers in one-to-few and one-to-many engagements for internal and external audiences. You will leverage your technical depth to craft clear, compelling, and highly differentiated messaging by working backward from customer requirements. We are looking to speak to candidates who are based in Dublin for our hybrid working model. What You’ll Do Drive Strategy & Execution: Act as the strategic owner for MongoDB’s context engineering portfolio—MCP Server, Agent Skills, VoyageAI, and more— aligning roadmap and go-to-market with MongoDB’s long-term business goals, in collaboration with Product Management, Engineering, Developer Relations, Partn

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

The Team MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently. You will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll join a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture. This role can be based out of either our Dublin or Cork office or remotely in Ireland. The ideal candidate should Have 6+ years of experience working on software development and operating distributed systems Proficiency in Python, Go, or a similar language Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs. Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Responsibilities Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineering needs Build for reliability, making services and infrastructure avail

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

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The Internal System Org is at the core of Stripe to empower business-critical financial domains including Finance and Strategy, Accounting, Tax, Treasury, Product Experience, and GTM. We are the Financial Enablement team, acting as the centralized data analytics team for Internal System Org. We enable and empower Finance and Strategy, GTM, Accounting, and Product teams to achieve business goals through dataset development, data analytics support, dashboards, AI, and operational efficiency enhancements. What you'll do You're passionate about solving business problems and making a direct impact on the business. You thrive in environments with many moving parts and quickly pick up new domain knowledge and technologies (e.g., AI). We're looking for someone with strong communication skills and advanced SQL and analytics abilities. A background in Accounting or Finance, or prior AI experience, is a strong plus, though these can also be developed on the job. Responsibilities Perform data analysis, identify trends, conduct research, and build visualizations to deliver objective, critical insights that fulfill team stakeholders' business needs Work closely with cross-functional teams, including Finance and Strategy, Accounting, Product, Tax, User Billing, Seller System, and Sales Ops teams, to align on financial goals and drive revenue growth Work closely with Engineering and Product teams to help define product solutions Leverage AI tools to improve

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 Fluent in written and spoken Spanish and English Datadog values people fr