Top Tech Jobs & Startup Jobs in Dublin

Lead DevOps Engineer will build and operate cloud infrastructure and CI/CD pipelines to deploy and run foundation models and AI/data workloads. Responsibilities include infrastructure as code, container orchestration, monitoring, security best practices, Databricks support, incident response, and collaboration with AI, data, and software engineers to enable reliable, scalable production AI systems.

Build and operate scalable CI/CD pipelines, cloud infrastructure (primarily AWS), and runtime environments for foundation-model and data workloads. Automate deployments, manage IaC, container orchestration, Databricks integration, monitoring/observability, and secure pipelines. Collaborate with AI, data, and software engineers, troubleshoot production issues, and promote DevOps best practices for reliable model training and inference at scale.

Design, build, and deploy transformer-based and generative AI models into production. Develop data pipelines, feature engineering, training workflows, and model serving. Apply MLOps practices, collaborate with product and engineering teams, and support production troubleshooting and performance tuning.

Design, build, and deploy transformer and generative AI models into production. Develop data pipelines, feature engineering, training and inference workflows. Implement model serving, monitoring, and MLOps practices. Collaborate with product, data, and engineering teams, participate in code reviews, troubleshoot and tune models, and ensure production-grade performance and reliability.

Lead a distributed agile team to design, develop, and maintain high-performance, high-volume Java applications for commercial virtual payments. Define features, contribute to system development, ensure SLAs, mentor engineers, improve processes, and deliver secure, scalable API/Batch/UI solutions.

Design, build, and productionize transformer-based and generative AI models. Develop training and inference pipelines, integrate models into APIs, apply MLOps practices, monitor performance, and collaborate with product and engineering teams to deliver reliable AI solutions.

Lead SRE responsible for production readiness, reliability, scalability, automation, monitoring, incident response, root cause analysis, capacity planning, and CI/CD pipeline ownership. Mentor teams, enforce operational standards, partner with development to design resilient systems, reduce toil via automation, and drive observability and ITSM best practices across distributed applications.

Lead daily administration, monitoring, patching and troubleshooting of enterprise load balancers. Ensure configurations, PKI, and monitoring meet availability and security standards; automate builds and diagnostics; collaborate with engineering and delivery teams to design scalable application architecture and train operations staff.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, and inference APIs. Apply MLOps practices (tracking, versioning, testing, monitoring), collaborate with product and engineering teams, troubleshoot and optimize production models, and follow security and engineering standards.

Lead site reliability for Mastercard products: ensure production readiness, resilience, scalability and performance. Drive automation, CI/CD, monitoring, SLOs, capacity planning, incident response, root-cause analysis, and mentor teams to embed operational excellence throughout the development lifecycle.