Top Software Engineer Jobs in Dublin

Build and maintain Ergodic AI’s AI platform across back-end and front-end systems. The role involves developing with Python web frameworks and JavaScript/TypeScript, integrating with client technology stacks and workflows, applying AI, ML, and LLM concepts, and contributing to DevOps, cloud deployment, testing, and infrastructure practices. As an early-stage hire, the engineer will help shape the product and solve complex data and AI challenges.

Develop and maintain automated and manual tests for an AWS-based registry platform using C# and relational or non-relational databases. Collaborate with QA and engineering teams in an Agile environment, enhance automation frameworks, test XML and JSON APIs, configure TeamCity continuous integration, assist with AWS deployments through Azure DevOps, and maintain bugs, test plans, and estimates.

Supports integration of IT systems, tools, device data, and network logs into Salesforce Data360. Builds Agentforce workflows and automations using Python, Swift, Go, MuleSoft, and AWS. Integrates device-management APIs, troubleshoots serverless infrastructure, and collaborates with IT teams to improve employee experiences. Requires technical education or equivalent experience, API knowledge, AI interest, and familiarity with cloud and serverless environments.

Lead the architecture, design, development, and modernization of Mastercard’s cloud-native experimentation and analytics platform. Build scalable services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, Spark, and PySpark. Drive technical strategy, system design, code reviews, delivery, observability, security, and reliability across distributed teams while mentoring engineers and coordinating cross-functional initiatives.

Lead architecture, design, coding, testing, and delivery of scalable cloud-native software for Mastercard’s experimentation and analytics platform. Build distributed services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, and Spark. Drive modernization, technical strategy, architecture reviews, security, reliability, observability, and continuous delivery. Coordinate globally distributed teams, collaborate across engineering and business functions, and mentor engineers while championing engineering excellence.

Leads architecture, design, development, modernization, and delivery of scalable cloud-native experimentation and analytics software. Builds services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, Spark, and PySpark. Provides technical leadership across distributed teams, drives design and code reviews, mentors engineers, and champions security, reliability, observability, performance, and continuous delivery.

Lead architecture and hands-on development of Mastercard’s cloud-native experimentation and analytics platform. Design scalable services, APIs, data pipelines, and distributed systems using AWS, Azure, Databricks, and Spark/PySpark. Drive modernization, technical strategy, design reviews, delivery across global teams, and engineering best practices for security, reliability, observability, and performance. Mentor engineers and collaborate with product, data science, QA, security, and operations teams.

Leads architecture, design, development, and delivery of scalable cloud-native experimentation and analytics platforms. Builds distributed services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, Spark, and modern software practices. Drives modernization, technical strategy, architecture reviews, cross-team execution, reliability, security, observability, and continuous delivery while mentoring engineers and coordinating globally distributed teams.

Lead the architecture, design, development, and modernization of Mastercard’s cloud-native experimentation and analytics platform. Build scalable services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, and Spark/PySpark. Drive technical strategy, system design, code reviews, architecture decisions, and cross-team execution while mentoring engineers and ensuring secure, reliable, observable, high-performance software delivery.

Leads architecture, design, coding, testing, and delivery of a cloud-native experimentation and analytics platform. Builds scalable services, APIs, data pipelines, and distributed systems using AWS, Azure, Databricks, Spark, and Kubernetes. Drives modernization, technical strategy, architecture reviews, reliability, security, observability, and continuous delivery. Coordinates globally distributed teams, partners cross-functionally, mentors engineers, and ensures production-quality solutions aligned with enterprise standards.

Lead architecture, design, development, and delivery of scalable cloud-native experimentation and analytics platforms. Build distributed services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, Spark, and modern engineering practices. Drive modernization, technical strategy, design reviews, delivery coordination, reliability, security, observability, and continuous improvement. Mentor engineers and collaborate across product, data science, QA, security, operations, and globally distributed engineering teams.

Lead architecture, design, development, and delivery of Mastercard’s cloud-native experimentation and analytics platform. Build scalable services, APIs, data pipelines, and distributed systems using AWS, Azure, Databricks, Spark, and modern delivery practices. Drive modernization, technical strategy, design reviews, code quality, security, reliability, and observability. Coordinate globally distributed teams, collaborate with product and technical partners, mentor engineers, and deliver secure, high-performance software across the full development lifecycle.

Leads architecture, design, development, testing, and delivery of scalable experimentation and analytics software. Builds cloud-native services, APIs, data pipelines, and distributed systems using AWS, Azure, Databricks, and Spark. Drives modernization, technical strategy, architecture reviews, security, reliability, observability, and continuous delivery. Coordinates globally distributed teams, partners cross-functionally, mentors engineers, and ensures robust solutions align with enterprise standards.

Lead the architecture, design, development, and modernization of Mastercard’s cloud-native experimentation and analytics platform. Build scalable services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, Spark, and PySpark. Drive technical strategy, system design, engineering standards, code reviews, and delivery across global teams. Mentor engineers and improve scalability, reliability, observability, security, and developer productivity through modern software practices.

Build and operate backend services supporting millions of emails. Own features end to end, design reliable distributed systems, scale APIs and databases, manage cloud infrastructure, improve observability and deployments, and participate in on-call rotation. Collaborate with customers and support to improve the product, strengthen engineering quality, and deliver complete experiences across the stack.

Design, build, and operate core platform services to improve availability, scalability, latency, and cost efficiency. Develop platform primitives (infra, databases, queuing), enable developer experience, and implement tooling for observability, self-healing, configuration-as-code, and cost optimization.

Mid-level software engineer contributing to customer-facing Atlas Growth features. Build readable, well-tested TypeScript/React code, write database queries, author technical specs, lead small projects, collaborate with product and design, participate in reviews, triage support, and join on-call rotation.

Design and develop clean, maintainable software for automated document-processing products. Collaborate with business stakeholders to translate requirements into product improvements, conduct code reviews, guide technical direction, mentor colleagues, and improve engineering practices. The role uses Golang, MySQL, Docker, Kubernetes, cloud infrastructure, and GitHub CI/CD while emphasizing product ownership, clean architecture, software craftsmanship, and technical communication.

Design and deliver Java-based capabilities for Mastercard’s large-scale Decision Enrichments platform. Build secure, resilient distributed systems, REST APIs, microservices, and event-driven applications. Collaborate with product, architecture, quality, and engineering teams throughout design, testing, deployment, and operations. Troubleshoot production issues, improve platform architecture, apply engineering best practices, and use AI-assisted development practices. Contribute technical leadership, documentation, automation, observability, and continuous improvement for mission-critical payment decisioning systems.

Design and deliver Java-based capabilities for Mastercard’s large-scale decisioning platform. Build secure, resilient distributed systems, REST APIs, microservices, and event-driven solutions. Collaborate with product, architecture, business analysis, and quality teams throughout design, development, testing, deployment, and operations. Troubleshoot production issues, improve platform architecture, apply engineering best practices, and use AI-assisted development practices. Provide technical leadership while supporting continuous improvement and operational excellence.

Design and deliver Java-based capabilities for Mastercard’s large-scale Decision Enrichments platform. Build secure, resilient distributed systems, REST APIs, microservices, and event-driven solutions. Collaborate with product, architecture, quality, and engineering teams across the software lifecycle, including testing, deployment, operations, and troubleshooting. Contribute to technical design, automation, continuous improvement, observability, and engineering standards while applying AI-assisted development practices.

Design and deliver Java-based capabilities for Mastercard’s large-scale Decision Enrichments platform. Build secure, resilient distributed systems, REST APIs, and event-driven applications; collaborate with product, architecture, and quality teams; contribute to design, testing, deployment, documentation, and operational excellence. Troubleshoot production issues, improve engineering practices, evaluate technologies, and apply AI-assisted development throughout the software lifecycle.

Design and deliver Java-based capabilities for Mastercard’s high-scale Decision Enrichments platform. Build secure, resilient distributed systems and RESTful microservices, collaborate with cross-functional Agile teams, contribute to architecture and testing, troubleshoot production issues, improve automation and engineering practices, and apply AI-assisted development throughout the software lifecycle.

Designs and delivers Java-based capabilities for Mastercard’s large-scale Decision Enrichments platform. Builds resilient, secure distributed systems, APIs, microservices, and event-driven solutions; contributes across architecture, implementation, testing, deployment, and operations. Collaborates with product, architecture, quality, and engineering teams; troubleshoots production issues, improves platform capabilities, documents technical designs, and applies AI-assisted engineering practices. The role supports real-time decisioning for fraud prevention, risk management, payment intelligence, and customer experiences.

Design and deliver Java-based capabilities for Mastercard’s Decision Enrichments platform. Build scalable, resilient distributed systems, REST APIs, microservices, and event-driven applications. Collaborate with product, architecture, quality, and engineering teams throughout design, testing, deployment, and operations. Troubleshoot production issues, improve platform architecture, apply engineering best practices, and use AI-assisted development practices. The role requires technical leadership, enterprise-scale software expertise, and a focus on secure, high-performance payment decisioning systems.