Top AI & Machine Learning Jobs in Dublin

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 strategy, architecture, and delivery of a production-scale data platform enabling agentic AI and analytics. Design lakehouse, streaming, retrieval, vector/feature stores and MCP servers, ensure governance, observability, and secure AI data consumption, and manage senior data engineering teams.

Own and evolve Mastercard's AI-native data platform and applications: define roadmap, treat data as product with SLAs and governance, lead cross-functional teams, operationalize agentic AI and HITL workflows, ensure regulatory and security compliance, and translate regional customer needs into scalable data products.

Own and evolve an AI-native data platform and products: define roadmap and backlog, treat data as a product with SLAs and governance, transform structured/unstructured data into reusable schemas and datasets, lead cross-functional teams, operationalize agentic AI and HITL workflows, ensure compliance with security/privacy, translate regional needs into scalable models, analyze market trends, and drive product delivery within budget and timelines.

Lead product strategy and execution for Mastercard's AI-native data platform and products. Define roadmaps, data-as-product SLAs, governance, reusable data primitives and agentic AI/HITL workflows. Manage cross-functional teams, ensure compliance with security/privacy/regulatory requirements, translate regional needs, and deliver scalable data models, APIs, dashboards and datasets to meet business objectives.

Own and evolve Mastercard's AI-native data platform and products: define roadmaps, treat data as a product with SLAs and governance, lead cross-functional teams, operationalize agentic AI and HITL workflows, ensure compliance with security/privacy/regulatory teams, and translate regional requirements into scalable data models and datasets.

Own and evolve Mastercard's Data & AI platform and products: define roadmaps, treat data as a product, lead cross-functional teams, ensure governance and compliance, operationalize agentic AI and HITL workflows, translate regional requirements, and deliver scalable, high-quality data products.

Own and evolve an AI-native data platform and applications: define roadmap and backlog, treat data as a product with SLAs and governance, lead cross-functional teams to build reusable data primitives, ontologies and datasets, operationalize agentic AI and HITL workflows, ensure compliance with security/privacy/regulatory requirements, and translate regional customer needs into scalable solutions.

Own and evolve an AI-native data platform and applications: define roadmap, treat data as product, establish SLAs and governance, lead cross-functional teams, operationalize agentic AI and HITL workflows, ensure compliance, and translate regional needs into scalable data products.

Own and evolve an AI-native data platform and products: define roadmap, treat data as product with SLAs and governance, lead cross-functional teams to build reusable data primitives, ontologies, APIs and workflows, operationalize agentic AI/HITL processes, ensure compliance and stakeholder alignment, and drive product strategy and delivery.