Top React Jobs in Dublin

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 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.

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.

The Staff Software Engineer will design and develop frontend experiences for retail, collaborating with cross-functional teams and mentoring others while ensuring high-quality, scalable features.

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.

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, build, and own highly scalable, highly available messaging infrastructure that processes hundreds of millions to billions of messages daily. Collaborate across teams on architecture, performance, monitoring, and reliability; mentor engineers; improve development and experimentation processes; participate in hiring and technical design.

Design, build, and own features and services for Klaviyo's large-scale messaging platform. Drive performance, scalability, monitoring, and reliability for a pipeline that delivers hundreds of millions to billions of messages. Collaborate across teams, mentor engineers, and participate in hiring and technical process improvements.

Lead technical design and delivery of Klaviyo's messaging pipeline, building scalable backend services (Python/Go), driving architecture, mentoring engineers, collaborating across product, compliance, and platform, and ensuring high-throughput, reliable message delivery at scale.

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.

Design and build scalable, production-grade agentic AI applications and platform capabilities. Apply AI and agentic patterns to improve developer productivity across the SDLC, build cloud-native services, automate PDLC/CI-CD workflows, and partner with product and data science to deliver secure, reliable, production AI solutions.

Design and build tooling, services, and reusable patterns to apply generative and agentic AI to products and developer workflows. Implement AI-enabled apps and integrations, evaluate models and frameworks, improve developer experience through automation, and prototype and scale solutions in collaboration with product and engineering stakeholders.

Build and scale agentic AI tooling, services, and integrations. Design AI-enabled applications and developer workflows, evaluate models and frameworks, prototype products, and improve developer experience through automation and platform-level patterns.

Lead design and deliver production-ready agentic AI applications and cloud-native services. Define engineering patterns for reliability, observability, security, and cost control. Drive end-to-end SDLC, mentor engineers, collaborate with AI, product, and platform teams, and operationalize AI solutions from prototype to governed production.

Lead hands-on design and delivery of agentic AI applications and platform capabilities. Define engineering patterns for production AI systems, drive end-to-end SDLC, improve AI-enabled developer workflows, ensure security, observability, resiliency and cost control, mentor engineers, and collaborate with product, data science, and security teams to move prototypes to governed production.

Design and build production-grade, AI-enabled and agentic applications and platform capabilities. Apply agent orchestration, prompt/context management, and AI tooling to improve developer productivity. Build cloud-native services with reliability, observability, security, and CI/CD. Partner with product, data science, and engineering to move prototypes to production and drive platform-level engineering improvements.

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 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.

Design and build scalable, production-grade AI and agentic applications and platform capabilities. Improve engineering productivity via AI-assisted workflows, CI/CD, automation, and observability. Collaborate with product, data science, and engineering teams to move AI solutions from prototype to production while ensuring security, reliability, and maintainability.

Build tooling, services, and reusable patterns to apply generative and agentic AI to products and developer workflows. Design and implement AI-enabled applications, evaluate models and frameworks, improve developer experience via automation, and partner with stakeholders to prototype and scale AI solutions.

Design, build, and productionize scalable AI and agentic applications and platform capabilities. Apply agent orchestration, prompt/context management, RAG, inference APIs, and AI tooling to improve developer productivity. Deliver cloud-native services using Kubernetes and managed AWS/Azure services, ensuring reliability, observability, security, and maintainability. Partner with product, data science, and engineering teams to translate ideas into production-grade solutions and drive technical innovation.

Build tooling, services, and reusable patterns to apply generative and agentic AI across Mastercard. Design and implement AI-enabled applications and developer-facing workflows, evaluate models and frameworks, deliver prototypes to production, improve developer experience through automation, and collaborate with product and business stakeholders to scale AI solutions.

Design and build production-grade, AI-enabled and agentic applications and platforms. Apply agent orchestration and generative-AI patterns to improve developer productivity, reliability, and observability. Partner with product, data science, and engineering teams to take prototypes to production, automate PDLC/SDLC, and evaluate emerging tools while maintaining security, performance, and governance.

Design and build scalable, production-grade AI and agentic applications and developer platforms. Apply agentic patterns and AI tooling to improve engineering productivity, productionize AI solutions, and drive automation, CI/CD, reliability, and governance across the software development lifecycle.