Top Tech Jobs & Startup Jobs in Dublin

Design and manage public and on-prem cloud infrastructure, build and optimize CI/CD pipelines, champion Infrastructure as Code, drive monitoring and reliability, collaborate with R&D to troubleshoot and scale a high-volume, low-latency decisioning platform, and lead DevOps automation and cost-optimization efforts.

Lead global Quality Engineering for CNPF products and platforms. Define and execute QE strategy across full-stack, data/ML, and infrastructure; drive test automation, shift-left/right practices, release gates, incident root-cause analysis, tooling decisions, budgeting, and talent development.

Lead strategy, architecture, and delivery of a production-scale data platform enabling agentic AI and analytics. Build lakehouse, streaming, retrieval, vector/feature stores, MCP servers, and knowledge graphs. Ensure governance, lineage, data quality, observability, and AI-specific controls. Partner with Applied AI, Product, and Architecture; set standards for data products exposed to agents; remain hands-on to unblock teams and grow senior data engineering talent.

Lead and scale a global Quality Engineering organization across full-stack applications and data/ML platforms. Define QE strategy, drive test automation, embed shift-left/right practices, establish AI/ML evaluation frameworks, own release quality gates, manage budget/vendor relationships, and hire and develop QE leadership.

Lead strategy, architecture, and delivery of Mastercard's data platform for analytics and agentic AI. Design lakehouse, streaming, retrieval, vector/feature stores, MCP servers, and governance for real-time, secure, production-scale AI consumption. Guide senior engineers and partner with Applied AI, Product, Architecture, and Security.

Lead strategy, architecture, and delivery of a production-scale data platform enabling agentic AI and analytics. Architect retrieval pipelines, vector stores, feature and knowledge-graph integrations, lakehouse and streaming (Databricks, Spark, Kafka) on AWS. Ensure governance, lineage, data quality, observability and AI-specific controls. Partner with Applied AI and Product, set standards for data products exposed to agents, and guide a team of senior data engineers while remaining hands-on for architectural decisions.

Lead and scale Quality Engineering across full-stack and data/ML platforms. Define QE strategy, drive test automation, shift-left/right practices, establish AI/ML and data quality frameworks, own release quality gates, perform root-cause analysis, manage budget/vendors, and hire and develop global QE talent to ensure product reliability and customer experience.

Lead data engineering strategy and delivery for CNPF, building lakehouse, streaming, retrieval, vector/feature stores and MCP servers to support agentic AI, LLMs, and analytics. Ensure governance, observability, security, and real-time data access while guiding senior engineers and partnering with Applied AI, Product, and Architecture.

Lead and scale Quality Engineering across full-stack and data/ML products. Define QE strategy, drive test automation, shift-left/right practices, release gates, root-cause analysis, and AI/ML guardrail testing. Manage budget, vendors, hiring, and career paths while improving product reliability and customer experience.

Design, provision, and operate high-volume, low-latency decisioning infrastructure across cloud and on-prem. Build CI/CD pipelines, IaC, container orchestration, observability and automation. Collaborate with global R&D, troubleshoot production issues, drive DevOps best practices, cost optimization, and lead technical initiatives.