Top React Jobs in Dublin

Leads applied AI and data science initiatives, designing and developing machine learning, deep learning, NLP, and LLM solutions. Builds prototypes, products, architectures, and pipelines; researches emerging AI technologies; mentors junior data scientists; collaborates globally on innovation and R&D; communicates technical direction; and contributes to research papers and patents.

Lead end-to-end design and delivery of full-stack, scalable React and Java/Spring Boot solutions. Drive API contracts, microservices architecture, CI/CD, observability, security and performance standards. Mentor engineers, own production readiness and SLOs, and partner with product and architecture to improve engineering quality and delivery across teams.

Develop and maintain secure, scalable backend services, RESTful APIs, and integrations supporting internal platforms, data products, and customer applications. Collaborate with product, architecture, data engineering, and data science teams; participate in design, testing, code reviews, CI/CD, production support, troubleshooting, and root cause analysis. Apply secure coding, observability, automation, and reliability practices across the software development lifecycle.

Leads the planning, architecture, development, and delivery of scalable, secure software solutions for Mastercard’s Emerging Data Signals product. Drives AI and emerging-technology innovation from research through production, champions delivery automation, supports customer integrations, and provides technical leadership. Collaborates with globally distributed engineering, data, product, operations, and customer teams while improving platform performance, reliability, security, and customer experience.

Lead Data Scientist developing high-performance AI solutions using machine learning, deep learning, NLP, and large language models. Responsibilities include researching emerging frameworks, creating prototypes and products, designing AI architectures and pipelines, developing APIs, collaborating across global teams, publishing research, filing patents, mentoring data scientists, and leading project delivery. The role requires strong Python, SQL, cloud, software engineering, and MLOps capabilities.

Designs, develops, tests, and maintains backend services, RESTful APIs, and integration components. Builds secure and scalable solutions, collaborates with product, architecture, data engineering, and data science teams, and supports CI/CD, automation, monitoring, production troubleshooting, and root cause analysis. The role contributes to software quality, reliability, secure coding, and continuous engineering improvements.

Lead design and delivery of full-stack, high-performance solutions (Java Spring Boot + React). Architect scalable microservices and UI systems, define APIs, CI/CD and observability standards, mentor engineers, own production readiness, and drive cross-team delivery and engineering quality improvements.

Leads the planning, architecture, development, and delivery of scalable software solutions for global customers. Drives AI and emerging-technology initiatives from concept through production, champions automation across the software lifecycle, and supports secure, resilient platform operations. Collaborates with engineering, data, product, operations, and customer teams while serving as a technical subject matter expert for integrations and solution adoption.

Develop and maintain secure, scalable backend services, RESTful APIs, and integration components. Collaborate with product, architecture, data engineering, and data science teams to deliver production-ready solutions. Participate in design, testing, code reviews, CI/CD, monitoring, troubleshooting, root cause analysis, and reliability improvements while following security, privacy, and compliance standards.

Leads applied data science and AI research to design, develop, and prototype high-performance solutions using machine learning, deep learning, NLP, and large language models. Responsibilities include researching emerging AI technologies, building solution architectures and pipelines, developing APIs and interfaces, optimizing SQL, collaborating across global teams, publishing research, filing patents, identifying AI opportunities, mentoring junior scientists, and leading projects or small teams.

Lead applied AI and data science research within Mastercard Foundry, developing high-performance solutions using machine learning, deep learning, NLP, and large language models. Responsibilities include designing architectures and prototypes, researching emerging AI technologies, building APIs and pipelines, collaborating globally, mentoring junior scientists, presenting technical direction, and contributing to research papers and patents.

Lead Data Scientist developing high-performance AI solutions using machine learning, deep learning, NLP, and large language models. Responsibilities include researching emerging AI technologies, building prototypes and products, designing solution architectures and pipelines, optimizing APIs and SQL, collaborating across global teams, publishing research, filing patents, mentoring junior scientists, and leading project delivery. The role also involves identifying AI opportunities and applying cloud, MLOps, and software engineering practices.

Leads the planning, architecture, development, and delivery of scalable, secure software solutions for Mastercard’s Emerging Data Signals product. Drives AI and emerging-technology initiatives from research through production, champions automation across the software lifecycle, collaborates with global engineering and business teams, and provides technical leadership for customer integrations and platform adoption.

Lead design and delivery of full-stack, high-performance solutions (Java Spring Boot + React). Architect scalable microservices and UI components, define APIs and CI/CD, ensure reliability, security, observability, and production readiness, mentor engineers, and drive cross-team delivery and engineering quality.

Lead Data Scientist developing high-performance AI solutions using machine learning, deep learning, NLP, and large language models. Responsibilities include researching emerging AI technologies, building prototypes and products, designing AI architectures and pipelines, contributing to patents and research papers, mentoring junior scientists, presenting technical direction, and collaborating globally on innovation and R&D initiatives.

Leads the planning, architecture, development, and delivery of scalable software solutions for global customers. Drives AI and emerging technology initiatives from concept through production, champions automation across the software lifecycle, and supports secure, resilient platform operations. Collaborates with engineering, data, product, operations, and customer teams while serving as a technical subject matter expert for Emerging Data Signals.

Lead design and delivery of full-stack React and Java/Spring solutions. Architect scalable microservices, define APIs and UI patterns, set CI/CD, observability and security standards, mentor engineers, own production readiness and SLOs, and drive cross-team delivery and engineering quality.

Lead the planning, architecture, and delivery of scalable software solutions for Mastercard’s Emerging Data Signals product. Drive AI and emerging-technology initiatives from concept through production, champion automation across the software lifecycle, collaborate with global engineering and product teams, and provide technical leadership for customer integrations. Ensure solutions are secure, resilient, maintainable, and aligned with enterprise standards.

Develop and maintain secure, scalable backend services, RESTful APIs, and integrations supporting data, analytics, and AI-enabled capabilities. Collaborate with product, architecture, data engineering, and data science teams to deliver production-ready solutions. Responsibilities include software design, coding, testing, code reviews, CI/CD automation, troubleshooting, root cause analysis, observability, secure coding, and production support.

Develops production-ready agentic AI systems and scalable integrations using AI-first software engineering practices. Evaluates models, tools, and emerging standards while building across the full SDLC. Presents demos, workshops, and technical thought leadership to engineers and executives, collaborates in an R&D environment, mentors colleagues, and promotes developer experience, security, and code quality.

Design, develop, and test scalable backend systems with a development-first mindset. Build and maintain test automation across API and UI layers, enhance CI/CD pipelines, support performance, security, and operability engineering, troubleshoot complex systems, and drive quality-first engineering practices across the development lifecycle.

Design, build, and test scalable backend systems with a development-first mindset. Implement and maintain API and UI automation frameworks, enhance CI/CD pipelines, drive shift-left testing, support performance, security, and reliability engineering, and collaborate on architecture and observability to ensure production-grade quality and high system availability.

Senior Software Engineer responsible for development-first quality engineering: build scalable backend systems, design and implement API/UI test automation, enhance CI/CD pipelines, drive shift-left testing, contribute to architecture, performance, security, observability, and troubleshoot distributed systems to ensure high reliability.

Build AI-first, production-ready software and agentic AI systems using multi-agent workflows, tool-calling, and orchestration. Evaluate AI models, develop scalable integrations, and apply emerging standards such as MCP and AGENTS.md. Serve as an AI developer advocate through demos, workshops, and executive presentations. Collaborate in an R&D environment, mentor engineers, promote developer experience and code quality, and accelerate innovation across Mastercard.

Design, develop, and test scalable backend systems with a development-first mindset. Build and maintain API/UI automation frameworks, enhance CI/CD pipelines, drive shift-left testing, support performance/security/reliability efforts, perform code reviews, troubleshoot distributed systems, and promote quality-first engineering practices across teams.