Top React Jobs in Dublin

Build and ship Agentic AI tooling, services, and reusable patterns to enable AI-enabled applications and developer workflows. Design and implement AI orchestration, tool-calling, and context management, evaluate models and SDKs, improve developer experience via automation and CI/CD, and partner with product and business teams to prototype, validate, and scale production solutions.

Build platform tooling, services, and reusable patterns to apply generative and agentic AI across products. Design and implement AI-enabled applications, evaluate models and frameworks, improve developer experience through automation and CI/CD, and partner with stakeholders to prototype, validate, and scale AI solutions.

Build and ship AI-enabled applications, tooling, and platform capabilities for agentic AI. Design reusable services, evaluate models and frameworks, improve developer workflows, and partner across product and engineering to prototype and scale AI solutions.

Build tooling, services, and reusable patterns to apply Generative and Agentic AI across Mastercard. Design and implement AI-enabled applications, evaluate models and frameworks, improve developer experience, and deliver prototypes to production in collaboration with product and engineering stakeholders.

Build tooling, services, and reusable patterns to apply generative and agentic AI across products. Design, implement, and evaluate AI-enabled apps and developer workflows; improve developer experience via automation and platform capabilities; partner with stakeholders to deliver prototypes to production and share best practices across Mastercard.

Lead engineer role building Agentic AI tooling, services, and reusable patterns. Design and implement AI-enabled applications and developer workflows, evaluate models and frameworks, build prototypes to production, improve developer experience through automation, and partner across product and engineering to scale AI solutions and share best practices.

Design, build, and scale agentic and generative AI tooling, services, and developer-facing platforms. Implement AI-enabled applications, evaluate models and frameworks, improve developer experience, and partner with product and business stakeholders to prototype and productionize solutions.

Build and ship Agentic AI tooling, services, and reusable patterns. Design AI-enabled applications and developer-facing capabilities, evaluate models and frameworks, improve developer experience with automation, and partner across product and engineering to prototype, validate, and scale AI solutions.

Design and build Agentic AI tooling, services, and reusable patterns. Implement AI-enabled applications and developer-facing capabilities, evaluate models and frameworks, develop frontend (React/Next.js) and backend (Java/Python) systems, improve developer experience via automation and CI/CD, and partner with stakeholders from prototype to validation while sharing best practices.

Lead engineer building tooling, services, and reusable patterns for Agentic and Generative AI. Design and implement AI-enabled applications, evaluate models and frameworks, improve developer experience through automation, and partner with product and business stakeholders to prototype, validate, and scale AI solutions.

Design, develop, and maintain secure, scalable production services. Produce architecture artifacts, implement REST APIs, operate services on AWS with containers and CI/CD, use AI-assisted dev tools responsibly, analyze data for system improvements, and ensure application resiliency and security.

Design and build scalable, production-grade AI and agentic applications and platform capabilities. Apply generative AI and agentic patterns to improve engineering productivity across the SDLC. Partner with product, data science, and engineering to turn prototypes into secure, reliable, maintainable production solutions.

Design and build scalable, production-grade AI and agentic applications and platforms. Improve engineering productivity via AI-enabled workflows, CI/CD, automation, and developer tools. Partner with product and data science teams to take prototypes to production while ensuring reliability, security, observability, and maintainability.

Design and build scalable, production-grade agentic AI applications and platform capabilities. Apply generative AI and agentic patterns to improve engineering productivity across the PDLC/SDLC. Collaborate with product, data science, and engineering teams to take AI-enabled solutions from prototype to production while ensuring reliability, security, and observability.

Design and build scalable, production-grade AI and agentic applications and platform capabilities. Improve engineering productivity via AI-assisted tooling and automation, drive AI-enabled solutions from prototype to production, and collaborate with product, data science, and engineering teams to deliver secure, reliable, and maintainable systems.

Design, build, and productionize AI-enabled, agentic applications and platform capabilities. Improve engineering productivity via AI-driven workflows, CI/CD automation, and developer tooling. Collaborate with product, data science, and engineering teams to deliver secure, reliable, scalable solutions.

Design and build scalable, production-grade AI and agentic applications and platform capabilities. Apply AI patterns to improve engineering productivity across the product lifecycle, drive CI/CD and automation, partner with product and data science, evaluate emerging tools, and take AI-enabled solutions from prototype to secure, reliable production.

Design and build scalable, production-grade agentic AI applications and platform capabilities. Improve engineering productivity via AI-assisted workflows, CI/CD, automation, and cloud-native services while ensuring reliability, security, and measurable business impact.

Design and build scalable, production-grade AI and agentic applications and platform capabilities. Improve engineering productivity via AI-enabled workflows, CI/CD, automated testing, and cloud-native services. Partner across product, data science, and engineering to move prototypes to reliable, secure, observable production systems.

Design and build production-grade agentic AI applications and platform capabilities. Apply generative AI patterns and AI-assisted developer tooling to improve engineering productivity, productionize AI solutions, and drive platform innovation with a focus on reliability, security, and measurable business impact.

Build scalable, production-grade AI and agentic applications and platform capabilities. Apply Generative AI and agent patterns to improve engineering productivity across the SDLC, productionize AI solutions with reliability, security, and observability, and partner with product, data science, and engineering teams to deliver measurable business value.

Design and build scalable, production-grade AI and agentic applications and platforms. Apply agent orchestration, generative AI, and developer tooling to improve engineering productivity. Partner across product, data science, and engineering to deliver secure, reliable, observable, and maintainable solutions from prototype to production.

Lead a hands-on engineering team to design and deliver IoT and edge-to-cloud solutions that integrate AI/ML for real-time workplace insights. Architect resilient, secure pipelines, enforce data governance (FAIR), drive agentic AI adoption across the SDLC, mentor engineering talent, and split time between strategic leadership and active coding.

Lead a product-aligned engineering organization to build and operate a cloud-native Talent Performance platform. Own technology direction, architecture modernization, integrations, delivery, reliability, security, and governance. Manage multiple cross-functional teams, vendor relationships, and stakeholder alignment. Drive adoption of AI-assisted engineering with appropriate controls while ensuring production readiness, observability, cost governance, and measurable engineering KPIs.

Build and enhance full-stack, cloud-native applications focused on Java, integrating LLM/generative AI and IoT device data. Design and deliver microservices, ensure operational stability, troubleshoot production issues, create architecture artifacts, analyze large datasets, and integrate smart-building and edge computing solutions to improve user experiences and efficiency.