Top Tech Jobs & Startup Jobs in Dublin

Build and lead scalable full-stack, data-intensive applications for analytics, experimentation, and decision-making. Responsibilities include team-level system design, distributed systems and API development, Databricks and Spark data processing, AI-powered agentic products using LLMs, performance optimization, cloud-native deployment, troubleshooting, secure coding, observability, CI/CD, and mentoring engineers.

Lead the architecture, development, and productionization of AI-powered products, intelligent agents, and cloud-native analytics platforms. Design agentic systems with reasoning, memory, retrieval, evaluation, safety, and human oversight. Build scalable services and APIs using AWS, Azure, Databricks, Spark, Python, and Java. Drive technical execution, architecture reviews, DevSecOps, testing, reliability, governance, and cost optimization while mentoring engineers and coordinating globally distributed teams.

Develop secure, reliable, and maintainable software for Mastercard’s payment systems. Contribute across the full software development lifecycle, from design through deployment, while owning monitoring, dependencies, builds, and production rollouts. Collaborate effectively in a global team and apply strong computer science, analytical, and problem-solving skills to deliver high-impact solutions.

Lead the architecture, development, and production deployment of AI-powered products, intelligent agents, and cloud-native analytics platforms. Build agentic workflows using LLMs, retrieval systems, orchestration, memory, evaluation, and safety controls. Develop scalable services and APIs with AWS, Azure, Databricks, Spark, Python, and Java. Drive engineering standards, CI/CD, security, observability, technical execution, architecture reviews, and mentorship across globally distributed teams.

Design and deliver Java-based capabilities for Mastercard’s large-scale Decision Enrichments platform. Build secure, resilient distributed systems, APIs, microservices, and event-driven applications. Collaborate with product, architecture, business analysis, quality, and engineering teams throughout design, testing, deployment, and operations. Troubleshoot production issues, contribute to technical architecture, improve engineering practices, automate delivery, document designs, and apply AI-assisted development practices.

Leads architecture and hands-on development of enterprise AI products, intelligent agents, agentic workflows, analytics platforms, and cloud-native services. Designs secure, scalable systems using LLMs, retrieval, orchestration, memory, evaluation, and safety controls. Guides productionization through reliability, observability, governance, CI/CD, testing, and cost optimization. Partners across engineering, product, data, security, and operations teams; coordinates global technical execution, drives design and code reviews, establishes reusable platforms, and mentors engineers.

Lead the architecture, development, and production deployment of AI-powered products, intelligent agents, and agentic workflows. Build scalable cloud-native services, APIs, analytics platforms, and distributed systems using AWS, Azure, Databricks, Spark, Python, and Java. Establish reliability, security, governance, observability, and cost-optimization practices while coordinating global engineering teams. Drive technical decisions, reviews, CI/CD, automated testing, modernization, reusable platforms, and mentorship across the engineering organization.

Designs, develops, tests, deploys, and supports scalable Java-based distributed systems for Mastercard’s real-time decisioning platform. Builds resilient microservices and APIs, collaborates in Agile teams, troubleshoots production issues, contributes to architecture and technical documentation, and promotes automation, DevOps, security, observability, and continuous improvement. The role also applies AI-assisted engineering practices across the software development lifecycle.

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.

Develop secure, reliable, and maintainable software for Mastercard’s payment systems. Contribute across the software development lifecycle, from design through deployment, while owning monitoring, dependencies, builds, and releases. Collaborate globally, solve complex problems, and apply computer science fundamentals to create high-quality applications with real-world customer impact.