Top Engineering Jobs in Dublin

Lead a team building API-driven microservices for virtual card management. Oversee design, development, code review, testing, security, performance engineering, cross-functional coordination, and people management to deliver resilient, scalable production software.

Lead a team to design, build, and deliver resilient, API-driven microservices at scale. Oversee project delivery, guide architecture and code quality, enforce testing and secure coding practices, coordinate cross-functional design decisions, and develop engineering talent through coaching and performance management.

Lead and manage a team building API-driven microservices for virtual card management. Oversee design, delivery, code reviews, testing strategies, security practices, performance engineering, and cross-functional architecture decisions while developing engineering talent.

Lead hands-on engineering for agentic AI products and platforms: define architecture and vision, build scalable agent frameworks, partner with Product/Data/Security, ensure production-grade reliability, observability, safety, and developer tooling to accelerate enterprise AI adoption.

Lead engineering for agentic AI products and platforms: define vision, build scalable agent frameworks, deliver production-grade LLM-powered systems, drive AI tooling adoption, ensure security/governance, and partner cross-functionally to operationalize agentic capabilities.

Lead a team to design, build, and deliver resilient, scalable API-driven microservices. Oversee project delivery, code reviews, SDLC best practices, testing (unit/integration/e2e), security, performance engineering, architecture decisions, and people management including hiring, coaching, and performance reviews.

Lead engineering strategy and hands-on delivery for agentic AI products and platforms. Build and scale teams and reusable agent frameworks, drive architecture for production-grade LLM/agent systems (context, memory, tool integration, orchestration, observability, safety), partner with Product and Data Science, and establish engineering standards, tooling, and measurable success criteria to move experiments into governed, scalable production.

Lead and deliver production-grade agentic AI systems and platforms. Define engineering vision, build and scale teams, architect agent frameworks and orchestration, ensure security, observability, and governance, partner with Product and Data Science, and drive adoption of AI tooling and developer productivity across the organization.

Lead a team to design, build, and deliver scalable, secure API-driven microservices. Oversee project delivery, code reviews, testing strategies, performance engineering, and operational resiliency while developing team members and coordinating cross-functional architecture decisions.

Lead engineering strategy and delivery for agentic AI products and platforms. Build and scale teams, drive architecture for production-grade agent systems, establish reusable frameworks, partner cross-functionally, and ensure security, observability, and governed AI adoption.

Lead engineering strategy and hands-on delivery for agentic AI products and reusable agent frameworks. Build and scale teams and cloud-native platforms, drive architecture for production-grade agent systems (memory, orchestration, tool integration, observability, safety), partner cross-functionally, establish engineering frameworks, and measure adoption, quality, and business impact.

Lead engineering strategy and hands-on delivery for agentic, LLM-powered systems and reusable AI platforms. Build and scale teams and frameworks for orchestration, retrieval, observability, safety, and production-grade deployment; partner with Product, Data Science, Security, and Platform teams to move agentic solutions from experimentation to governed, scalable production.

Lead engineering for agentic AI products and platforms: build and scale teams, define architecture and frameworks for LLM-driven agents, ensure production-grade reliability, observability, security, and cross-functional adoption of AI tooling and governance.

Lead and manage a software engineering team building API-driven microservices for virtual card management. Oversee project delivery, architecture, code review, testing strategies, secure coding, performance engineering, cross-functional coordination, and team development including goal setting and performance appraisals.

Lead engineering strategy and hands-on delivery for agentic AI and LLM-powered products. Build and scale platforms, reusable agent frameworks, and orchestration for production-grade agents. Partner with Product, Data Science, Security, and Platform teams to translate use cases into secure, observable, and reliable systems. Drive AI tooling adoption, engineering standards, lifecycle management, and developer experience while measuring adoption, quality, latency, resilience, and business impact.

Lead a team designing, building, and delivering resilient, scalable API-driven microservices. Oversee project delivery, code review, architecture, testing strategies, secure coding, performance engineering, cross-functional coordination, and team development.

Lead a team to design, build, and deliver API-driven microservices at scale; ensure code quality, testing, security, performance, and operational resiliency; drive architectural decisions, mentor engineers, and manage delivery and performance reviews.

Lead a team of engineers to design, build, and deliver scalable, resilient API-driven microservices. Oversee project delivery, architecture, code reviews, testing, security practices, performance engineering, and team development.

Lead and scale engineering teams to design, build, and productionize agentic AI systems and reusable platform capabilities. Define architecture, frameworks, observability, safety guardrails, and developer tooling to move LLM/agent solutions from experimentation to secure, scalable enterprise production while partnering with product, data science, security, and platform teams.

Lead engineering for production-grade agentic AI products and reusable agent frameworks. Drive architecture, platform capabilities (lifecycle, retrieval, observability, safety), team scaling, AI tooling adoption, and cross-functional delivery to turn experiments into secure, scalable enterprise solutions.

Lead a team of engineers to design, build, and deliver resilient, API-driven microservices at scale. Oversee project delivery, code reviews, testing strategies, security best practices, performance engineering, and cross-functional architectural decisions. Manage and develop team members, set goals, and drive operational excellence and SDLC improvements.

Design, build, and deploy production AI solutions including transformer-based and generative models. Build data pipelines, training workflows, model serving and inference, apply MLOps practices, collaborate with product and engineering teams, and monitor and tune models in production.

Design, build, and deploy production AI/ML solutions including transformer and generative models. Develop data pipelines, training workflows, model serving, and MLOps practices. Collaborate with product and engineering teams, perform evaluation and performance tuning, and ensure maintainable, production-grade AI systems.

Design, build, and deploy production AI solutions including transformer and generative models. Develop data pipelines, feature engineering, training workflows, model serving, and MLOps practices. Collaborate with product and engineering teams, participate in code reviews, and monitor/model performance in production.

Design, build, and deploy production AI/ML solutions including transformer and generative models. Implement data pipelines, feature engineering, training workflows, model serving, and MLOps practices. Collaborate with product and engineering teams, participate in code reviews, troubleshoot and optimize models in production.