Top Tech Jobs & Startup Jobs in Dublin

Design, implement, optimize, and maintain Azure-based database solutions. Automate deployments with IaC, ensure backup/recovery and compliance, monitor performance, troubleshoot issues, and collaborate with development teams for schema and query optimization.

Lead development and production deployment of AI and agentic systems. Build and operate ML services, pipelines, model serving, monitoring, evaluation, and retraining. Partner with data scientists to productionize models, ensure reliability, security, and governance, and collaborate with platform, security, and infrastructure teams. Provide technical influence and mentorship.

Join the Authentication team to build, operate and improve low-latency, high-throughput fraud decisioning services. Implement and maintain CI/CD pipelines, deploy and troubleshoot across AWS (EKS/Kubernetes), on-prem and hybrid environments, improve observability and reliability following SRE practices, automate operations, support multi-environment governance, and collaborate within an Agile team to deliver scalable, secure software.

Design, implement, and optimize Azure-based database solutions (SQL, Cosmos DB, PostgreSQL, Redis). Ensure high availability, backup/recovery, performance tuning, IaC-driven deployments (Terraform/Bicep), CI/CD integration, monitoring, security/compliance, and cross-team collaboration with documentation and knowledge sharing.

Senior Data Scientist who manages large datasets, develops and validates predictive models, applies statistical/ML techniques, builds dashboards/prototypes, conducts QA, documents code, and partners with business stakeholders to drive data-driven decisions.

Lead technical program management for Mastercard's Decision Management fraud platform. Plan, execute, and communicate medium-to-large Agile projects, manage cross-team delivery, assess technical impacts, document audit/PCI controls, and partner with business, architects, and engineers to deliver high-performance fraud and identity solutions.

Lead hands-on design, development, and production deployment of AI and agentic systems. Build and operate ML services, pipelines, and APIs; implement model serving, monitoring, evaluation, and retraining. Partner with data scientists to productionize models, ensure reliability, security, and governance, drive technical design reviews, and mentor engineers.

Lead design, build, and production deployment of AI and agentic systems. Implement and operate ML services, model serving, monitoring, evaluation, and retraining pipelines. Partner with data scientists to productionize models, ensure reliability, security, and governance, and collaborate with platform, security, and infrastructure teams.

Lead and coordinate global R&D programs, drive cloud and infrastructure standardization, automate operational reporting and dashboards using AI, maintain Jira hygiene, remove delivery blockers, track delivery health metrics, and support local initiatives and events to ensure timely program execution.

Lead daily administration, monitoring, patching and automation of enterprise load balancers and WAFs. Troubleshoot complex network and application traffic issues, design monitoring strategies, support build/deploy automation, and collaborate with engineering and delivery teams to ensure 99.999% platform availability and operational readiness.