Top React Jobs in Dublin

Lead and manage an engineering team on the Atlas Growth team to design, build, test, and ship new Atlas features. Define roadmaps with stakeholders, contribute to technical architecture, mentor engineers, and collaborate with product, design, and analytics to improve onboarding, monetization, and cluster management for B2B customers.

The Staff Software Engineer will develop AI agents for restaurant workforce management, utilizing Java or Kotlin and modern web technologies. Responsibilities include full-stack development, collaboration across teams, mentoring, and championing best practices in agent development.

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 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.

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.

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.

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.

Build and operate foundational, security-critical platforms and cloud-native systems at scale. Automate infrastructure, reduce operational toil, define SLIs and SLOs, improve observability and incident response, perform capacity and performance analysis, and develop preventative reliability solutions. Participate in on-call rotations, post-incident reviews, technical design, and mentoring while collaborating with product, platform, and security engineering teams.

Build and maintain the reporting and analytics layer for restaurant customers: backend services in Kotlin/Java, design GraphQL/REST APIs and platform frameworks, integrate AI-native features, work with data pipelines/OpenSearch, and collaborate cross-team to deliver useful, production-quality reporting experiences.

Develop secure, scalable internal applications for bank leadership using Java, Spring, AWS, Microsoft 365 integrations, and AI capabilities. Responsibilities include system design, application development, testing, API and service development, codebase analysis, data visualization, automation, and software stability improvements. The role operates in an agile environment and requires responsible use of AI-assisted development tools, secure coding, architecture knowledge, CI/CD familiarity, and collaboration across technology teams.

Lead development of scalable scheduling software for Toast’s restaurant workforce management product. Responsibilities include full-stack feature development, solution design, estimation, testing, debugging, technical reviews, mentoring developers, and collaboration with product managers, designers, customer success, and engineering stakeholders. The role also champions software quality and development practices, contributes to product decisions, and uses AI tools to improve engineering productivity. This is a hybrid position requiring two days per week in the Dublin office.

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.

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.

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 tooling, services, and reusable patterns to apply Generative and Agentic AI to products and developer workflows. Design and implement AI-enabled applications and integrations, evaluate models, develop prototypes from concept to validation, and improve developer experience through automation and platform capabilities while partnering with product and business stakeholders.

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.

Design and build Agentic AI tooling, services, and reusable patterns; implement AI-enabled applications and developer-facing capabilities; evaluate models and frameworks; improve developer experience via automation; 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 and ship Agentic AI tooling, services, and integrations that enable teams to prototype, validate, and scale AI-enabled products. Design orchestration, tool-calling, context management, and developer-facing workflows; evaluate models and frameworks for quality, cost, latency and reliability. Partner with product and engineering stakeholders to deliver reusable, production-grade patterns and improve developer experience through automation and platform thinking.