Top Engineering Jobs in Dublin

Build and lead scalable full-stack, data-intensive applications and AI-powered products using distributed systems, cloud technologies, Databricks, Spark, and LLMs. Responsibilities include system design, API and service development, performance optimization, mentoring engineers, technical troubleshooting, secure coding, testing, observability, CI/CD, and cross-functional collaboration. The role guides team-level architecture and delivers reliable analytics-driven solutions for global customers.

Designs and delivers Java-based capabilities for Mastercard’s large-scale Decision Enrichments platform. Responsibilities include developing distributed microservices, REST APIs, and event-driven systems; contributing to architecture, testing, deployment, observability, and operational excellence; troubleshooting production issues; collaborating with cross-functional Agile teams; evaluating technologies; and applying AI-assisted engineering practices. The role focuses on secure, resilient, high-performance software supporting payment intelligence, fraud prevention, and risk management.

Build and lead full-stack, data-intensive, analytics-driven applications for business experimentation and decision-making. Responsibilities include system design, distributed systems development, Databricks and Spark data processing, AI and LLM-powered products, performance optimization, cloud-native deployment, troubleshooting, testing, security, observability, CI/CD, and mentoring engineers.

Designs and delivers Java-based capabilities for Mastercard’s large-scale Decision Enrichments platform. Responsibilities include developing resilient distributed systems, REST APIs, microservices, and event-driven applications; collaborating in Agile teams; contributing to architecture, testing, deployment, and operational excellence; troubleshooting production issues; improving engineering practices; and using AI-assisted development throughout the software lifecycle.

Lead development of high-performance Java applications and backend and consumer-facing features for Mastercard’s cybersecurity platform. Responsibilities include designing solutions, supporting production incidents, defining features, conducting code reviews, integrating vendor and open-source products, contributing to cloud and microservices development, and mentoring junior engineers.

Lead development of high-performance, high-volume Java applications and backend and consumer-facing platform features. Responsibilities include direct software development, production support, incident resolution, feature definition, solution planning, code reviews, and technical guidance for junior engineers. The role requires expertise in Java, enterprise application servers, Spring, Kafka, SQL, Linux, cloud development, microservices, and Agile delivery processes.

Lead development of high-performance, high-volume Java applications and backend and consumer-facing platform features. Responsibilities include direct software development, production support, incident resolution, feature planning, code reviews, vendor and open-source integration, cloud and microservices development, and technical guidance for junior engineers. The role requires collaboration with technical leads, analysts, and business stakeholders while ensuring secure, reliable software delivery.

Lead Software Engineer responsible for developing high-performance, high-volume Java applications and backend and consumer-facing platform features. Duties include production support, feature planning, code reviews, software integration, technical guidance, and collaboration with engineering and business teams. The role requires expertise in Java, Spring, Kafka, SQL, Linux, cloud development, microservices, application servers, and Agile development processes.

Designs and develops scalable full-stack, data-intensive, analytics-driven applications and AI-powered products. Responsibilities include system architecture, distributed systems, APIs, Databricks and Spark development, LLM-based agentic workflows, performance optimization, cloud-native deployment, testing, observability, troubleshooting, and mentoring engineers.

Designs and develops scalable full-stack, data-intensive, analytics-driven applications and AI-powered products. Leads system design, builds distributed services and data pipelines with Databricks and Spark, develops LLM-based agentic workflows, resolves performance and reliability issues, and mentors engineers. Collaborates cross-functionally to deliver secure, maintainable cloud-native solutions using modern software engineering, testing, observability, and CI/CD practices.