Top Tech Jobs & Startup Jobs in Dublin

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.

Build, test, and deploy AI/ML solutions including transformer and generative models. Support data preparation, feature engineering, model training, serving, evaluation, monitoring, and integration into applications while applying software engineering and MLOps best practices.

Lead SRE efforts to ensure reliability, scalability, and performance of Mastercard applications. Drive operational readiness, automation, CI/CD, monitoring/SLOs, incident response, root-cause analysis, capacity planning, and mentor engineering teams to reduce toil and improve resilience.

Build, test, and deploy transformer-based and generative AI models. Support data preparation, feature engineering, training pipelines, model serving, evaluation, monitoring, and integration into applications using MLOps and software engineering best practices.

Lead administration, monitoring, patching, troubleshooting and automation of enterprise load balancer platforms. Ensure high availability, implement monitoring strategies, collaborate with engineering and delivery teams, and train operations staff to resolve complex network and application traffic issues.

Design, build, and deploy transformer-based and generative AI models into production. Develop training pipelines, feature engineering, model serving, and MLOps practices. Collaborate with product, data, and engineering teams, perform model evaluation and performance tuning, and maintain production monitoring and lifecycle management.

Lead backend engineer for Mastercard's commercial virtual payments platform. Own design, development, and maintenance of high-performance, high-volume Java services; define features with product and tech leads; implement REST/SOAP APIs; ensure SLAs, reliability, and cloud-native deployments; mentor team members and improve processes in an agile environment.