Top Engineering Jobs in Dublin

Lead global Quality Engineering across full-stack and data/ML platforms: define QE strategy, drive test automation, embed shift-left/right practices, own release quality gates, manage incidents, budgets, vendors, and build a high-performing QE organization.

Lead global Quality Engineering for CNPF products, defining QE strategy across full-stack, data/ML, and infrastructure. Build and manage teams, drive test automation, shift-left/right practices, establish AI/data quality frameworks, own release gates, conduct root-cause analyses, manage budgets/vendors, and represent QE externally.

Lead and scale a global Quality Engineering organization for CNPF products, defining QE strategy across full-stack and data/ML systems. Drive test automation, shift-left/shift-right practices, AI/agentic product evaluation, release quality gates, root-cause analysis, tooling and vendor decisions, budgeting, and talent development to improve product reliability and customer experience.

Lead and scale Quality Engineering across full-stack and data/ML platforms. Define QE strategy, drive test automation, shift-left/right practices, establish AI/data quality frameworks, manage releases, budgets, vendors, and build global QE talent.

Lead and scale Quality Engineering across CNPF products: build a global QE team, define and execute QE strategy, drive test automation, embed shift-left/right practices, ensure data and AI/ML product quality, own release quality gates, perform RCA on incidents, and manage budget, vendors, and hiring.

Lead strategy and delivery of the data platform powering analytics and agentic AI across business verticals. Architect lakehouse, streaming, retrieval, vector stores, feature stores, 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, and guide a team of senior data engineers while staying hands-on to unblock technical challenges.

Lead strategy, architecture, and delivery of CNPF data platform to power analytics and agentic AI. Design lakehouse, streaming, retrieval, vector/feature stores, MCP servers, and knowledge graphs. Ensure governance, lineage, data quality, observability, and secure AI consumption. Partner with Applied AI and Product, guide senior engineers, and remain hands-on to unblock architecture and production issues.

Lead strategy, architecture, and delivery of a production-scale data platform enabling agentic AI and analytics. Design lakehouse, streaming, retrieval, vector/feature stores, MCP servers, and governance to ensure real-time, secure, and auditable data for LLMs and analytics. Guide senior engineers and partner with AI, product, and security teams.

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 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. 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 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.

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.

Lead global Quality Engineering across CNPF products, define QE strategy, drive test automation, shift-left/right practices, ensure data/ML and AI product quality, manage release gates, incident RCA, budgets, vendors, and hiring.

Lead a full-stack engineering team building high-performance analytics applications and front-end visualizations on massive datasets. Define service-oriented architectures, scope and deliver large-scale features, mentor engineers, drive CI/CD and engineering practices, and collaborate with product and global teams to deliver production-ready microservices and data-driven products.

Lead and manage multiple engineering squads building cloud-native Java/Spring Boot payment network services. Oversee deliverables, product and solution architecture for scalable real-time event-driven systems, drive CI/CD, automation, quality and AI adoption, and coordinate cross-regional stakeholders.

Lead a multidisciplinary engineering team to design, build and deliver scalable AI and quantum-enabled payment products. Define requirements, drive project execution using agile and AI-assisted processes, mentor engineers, coordinate with data scientists, and represent the team internally and externally.

Manage and coach scrum teams to design, build, and operate Java-based, distributed B2B payment applications. Own product initiatives from requirements to production, drive agile practices, ensure performance, security and reliability, collaborate with product and operations stakeholders, and communicate status to senior management.

Lead and coach scrum teams to deliver high-availability, high-volume commercial payments software. Oversee development, drive technical and agile best practices, communicate status to product, customers and senior management, and ensure compliance and security responsibilities.

Lead and manage multiple engineering squads building cloud-native, real-time payment solutions using Java and Spring Boot. Drive architecture, quality (automation, CI/CD), AI adoption, cross-region coordination, stakeholder reporting, and delivery metrics to ensure scalable, high-quality product outcomes.

Lead a multidisciplinary engineering team building scalable Quantum and AI/ML-enabled payment products. Define requirements, drive agile delivery, research/design solutions, manage projects, coach talent, and engage with external partners and events.