Top React Jobs in Dublin

Design, build, and maintain scalable full-stack, data-intensive applications and APIs. Develop and optimize data pipelines using Databricks/Spark, participate in architecture and code reviews, resolve performance bottlenecks, collaborate with cross-functional teams, mentor peers, and drive engineering best practices and operational excellence.

Lead a small full-stack engineering team to design, build, and deliver high-performance analytic applications and visualizations on large transaction datasets. Define service-oriented architectures, scope features, mentor engineers, drive CI/CD and engineering quality, and collaborate with product and global teams to deliver scalable microservice-based solutions.

Lead a small engineering team building high-performance analytics applications and visualizations on large datasets. Define architectures, scope features, mentor engineers, drive CI/CD and engineering best practices, collaborate with product and global teams, and deliver scalable microservice-based solutions that impact business outcomes.

The Engineering Manager will lead the PASS team, overseeing the development of the purchase and subscription experience, managing a full-stack team, and collaborating with cross-functional partners to drive revenue through innovative solutions and continuous improvement.

Design, build, test, and deploy full-stack product experiences for UK customers. Write clean, maintainable code, collaborate with product/design/support, and own feature delivery from design through deployment and iteration.

As a Principal Software Engineer, you will lead full-stack design of AI solutions, drive architecture, mentor engineers, and collaborate across teams to solve complex problems at Toast.

Mid-level software engineer contributing to customer-facing Atlas Growth features. Build readable, well-tested TypeScript/React code, write database queries, author technical specs, lead small projects, collaborate with product and design, participate in reviews, triage support, and join on-call rotation.

Design and build production-grade AI and agentic applications and developer platforms. Apply agent orchestration, LLMs, and AI-assisted workflows to improve engineering productivity. Build reusable services, ensure security, reliability, and observability, and drive CI/CD, automation, and developer experience across cloud-native environments.

Design and build production-grade, AI-enabled and agentic applications and developer platforms. Apply agentic/LLM patterns to improve engineering productivity, drive CI/CD and automation, ensure reliability, security, observability, and scalability, and create reusable frameworks and services across cloud-native environments.

The Senior Software Engineer will develop observability tools for MongoDB, enhancing user insight into database performance and reliability while tackling large-scale system challenges.

Design and build automated data migration solutions at cloud scale for MongoDB Atlas. Collaborate with teams to enhance features, solve technical challenges, and mentor others.

Design and build production-grade AI and agentic applications and developer platforms. Apply agent orchestration, LLMs, and AI-assisted workflows to improve engineering productivity. Deliver scalable, secure, observable services in cloud-native environments and drive reusable frameworks, CI/CD automation, and engineering best practices.

Design and build production-grade AI and agentic applications and developer platforms. Apply agentic patterns, CI/CD, automation, and AI-assisted workflows to improve developer productivity, reliability, security, and observability. Partner across product, data science, and engineering to take AI solutions from prototype to production and create reusable services and frameworks.

Design and build production-grade AI and agentic applications and platforms. Apply agentic patterns and AI tooling to improve developer productivity, automate PDLC/SDLC, ensure reliability, security, and observability, and create reusable frameworks and services across cloud-native environments.

Design and build scalable, production-grade AI and agentic applications and developer platforms. Apply agentic patterns and AI tooling to improve engineering productivity, reliability, security, and observability. Partner across product, data science, and engineering to take AI-enabled solutions from prototype to production, build reusable frameworks, and drive engineering standards and automation across the software development lifecycle.

Build scalable, production-grade AI and agentic applications and developer platforms. Design reusable services and frameworks, improve engineering productivity via AI-assisted workflows, ensure reliability, security, and observability, and partner across product, data science, and engineering to take AI-enabled solutions from prototype to production.

Design and build scalable production systems and developer platforms that leverage generative AI and agentic workflows. Implement cloud-native services, CI/CD, automation, observability, and security to productionize AI-enabled solutions. Partner with product and data science to deliver reusable frameworks, improve engineering productivity with AI-assisted workflows, and drive architecture and best practices across teams.

Design and build production-grade AI and agentic applications and developer platforms. Apply agent orchestration and AI-assisted workflows, drive automation and CI/CD, ensure reliability, security, and observability, and create reusable services that improve developer productivity and scale AI-enabled solutions across the organization.

Design and build production-grade agentic AI applications and platform capabilities. Apply AI patterns to improve engineering productivity, automate PDLC/SDLC, ensure reliability/security/governance, partner cross-functionally, and deliver reusable frameworks and services for scale.

Lead hands-on design and delivery of secure, scalable agentic AI applications and cloud-native services. Define engineering patterns for production AI systems, drive end-to-end SDLC, improve developer workflows with AI, mentor engineers, and collaborate with product, AI, security, and platform teams to move prototypes to governed production.

Lead design and deliver production-grade agentic AI applications and platform capabilities. Drive architecture, implementation, observability, security, CI/CD, and cross-functional delivery while mentoring engineers and shaping roadmaps for scalable, reliable AI-powered services.

Lead hands-on design and delivery of secure, scalable agentic AI applications and platform capabilities. Drive architecture, implementation, SDLC, observability, security, and cross-functional collaboration to take AI solutions from prototype to governed production. Mentor engineers and shape roadmaps to enable reliable, maintainable, and high-impact product delivery.

Lead design and deliver production-grade agentic AI applications and cloud-native services. Define engineering patterns, ensure security, observability, and reliability, drive SDLC improvements, mentor engineers, collaborate with AI, product, and platform teams, and move prototypes to governed production.

Lead design and deliver production-ready agentic AI applications and platform capabilities. Define engineering patterns, drive end-to-end SDLC, mentor engineers, ensure security, observability, reliability, cost controls, and collaborate with Product, Applied AI, Data Science, and stakeholders to move AI solutions from prototype to governed production.

Lead hands-on design and delivery of production AI/agentic applications and cloud-native services. Define engineering patterns for reliability, security, observability, and governance. Drive end-to-end delivery, mentor engineers, collaborate with Applied AI, Product, Security, and Platform teams, and shape technical roadmaps to scale AI-enabled products.