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 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.

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.

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 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.

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.

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 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.

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.

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.

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.

Develops production-ready agentic AI systems and scalable integrations using AI-first software engineering practices. Designs multi-agent workflows, evaluates AI models, applies emerging standards, and works across the full software development lifecycle. The role also includes developer advocacy through demos, workshops, thought leadership, and executive presentations, while mentoring engineers and advancing code quality, developer experience, and innovation.

Develop production-ready agentic AI systems and scalable software using AI-first practices across the full software development lifecycle. Evaluate AI models, build multi-agent workflows and integrations, and apply emerging standards such as MCP and AGENTS.md. The role also involves demos, workshops, executive presentations, developer advocacy, mentoring, and collaboration in an R&D environment.

Develops production-ready Agentic AI systems and scalable software integrations using AI-first practices across the SDLC. Evaluates AI models and emerging frameworks, applies standards such as MCP and AGENTS.md, and uses modern AI tooling. The role also includes product ideation, stakeholder presentations, demos, workshops, thought leadership, developer advocacy, mentoring, and collaboration with engineering leadership and executives.

Designs and builds agentic AI systems and scalable software integrations using modern AI tools and orchestration patterns. Evaluates AI models, applies emerging standards, and works AI-first across the software development lifecycle. The role also involves developer advocacy through demos, workshops, thought leadership, and executive presentations. Responsibilities include production software engineering, mentoring, improving developer experience and code quality, and collaborating in an R&D environment to accelerate product innovation.

Develop production-ready agentic AI systems and scalable software integrations using AI-first practices across the software development lifecycle. Evaluate AI models and emerging tools, apply standards such as MCP and AGENTS.md, and collaborate in an R&D environment. Deliver demonstrations, workshops, and thought leadership to engineering leaders and executives while mentoring teammates and advancing developer experience, code quality, security, and innovation.

Develop production-ready agentic AI systems and scalable software using AI-first practices across the full SDLC. Evaluate AI models, build multi-agent workflows and integrations, apply emerging standards, and deliver demos, workshops, and thought leadership to engineering and executive audiences. The role also involves mentoring, developer advocacy, innovation, and collaboration across Mastercard Foundry and the broader organization.

Develop AI-first software and agentic AI systems using multi-agent workflows, tool-calling, and orchestration. Build scalable production integrations, evaluate AI models, and apply emerging standards. Deliver demos, workshops, and thought leadership to technical and executive audiences while collaborating across Mastercard. The role also requires modern full-stack engineering, cloud-native development, security awareness, mentoring, and strong communication in an R&D environment.

Develop AI-native, production-ready software, including agentic AI systems, multi-agent workflows, tool-using agents, and integrations. Evaluate AI models, apply emerging standards, and work across the full software development lifecycle. Deliver demos, workshops, and thought leadership to engineering leaders and executives while mentoring colleagues and advancing developer experience, code quality, and innovation.

Designs and builds agentic AI systems, multi-agent workflows, tool-using agents, and scalable production software. Evaluates AI models, applies emerging AI standards, and develops integrations using modern software engineering technologies. Acts as an AI developer advocate through demos, workshops, and executive presentations while mentoring engineers, promoting developer experience, and driving innovation in an R&D environment.

Develop backend and full-stack observability tools for MongoDB Atlas, including metrics collection, slow-query monitoring, and database performance recommendations. Design scalable web applications, troubleshoot production issues, lead medium-sized technical projects, collaborate with customers and support engineers, participate in on-call rotations, and improve engineering practices and operational systems.

Lead and deliver secure, scalable cloud-native software across Python/Node.js/React stack. Design, develop, test, and operate production services, mentor engineers, drive architecture and CI/CD/IaC standards, and champion responsible AI-assisted engineering practices and operational stability.