Top Engineering Jobs in Dublin

Design, build, and operationalize transformer-based and generative AI models; develop training and inference workflows, data pipelines, and MLOps practices; deploy and monitor models in production; collaborate with product and engineering teams.

Design, develop, and productionize transformer-based and generative AI models. Build training workflows, data pipelines, feature engineering, model serving, and MLOps practices. Collaborate with product, data, and engineering teams, perform code reviews, troubleshoot and optimize models in production, and maintain model lifecycle and monitoring.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, inference, and MLOps practices. Collaborate with product, data, and engineering teams, perform model evaluation and tuning, and ensure production reliability and monitoring.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, and MLOps practices. Collaborate with product, data, and engineering teams to operationalize and monitor model performance.

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

Design, build, and deploy transformer-based and generative AI models into production. Implement training pipelines, feature engineering, model serving, MLOps practices, monitoring, and collaborate with product, data, and engineering teams to ensure reliable, performant AI systems.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, and MLOps (tracking, versioning, testing, monitoring). Collaborate with product, data, and engineering teams, perform model tuning and troubleshooting, and follow security and engineering standards.

Design, build, and productionize transformer-based and generative AI models. Develop training workflows, data pipelines, feature engineering, model serving, and inference APIs. Apply MLOps best practices (experiment tracking, versioning, testing, monitoring). Collaborate with product, data, and engineering teams to translate requirements, perform performance tuning, and maintain production model reliability.

Design, build, and deploy transformer-based and generative AI models into production. Develop data pipelines, training workflows, model serving/inference, and MLOps practices. Collaborate with product, data, and engineering teams to integrate models into applications, run evaluations, troubleshooting, and performance tuning while following engineering standards.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, model serving/inference, and MLOps practices. Collaborate with product, data, and engineering partners, perform performance tuning, and ensure model reliability, monitoring, and lifecycle management.

Leads software engineering teams responsible for developing, operating, and maintaining payment cancellation systems. Manages complex projects, technical strategy, delivery metrics, architecture and code reviews, security compliance, stakeholder collaboration, and vendor tools. Builds and mentors engineering talent while ensuring quality, cost effectiveness, SLA performance, innovation, and timely delivery.

Leads a software engineering team responsible for building, operating, and maintaining payment cancellation services. Manages major projects, technical strategy, architecture, development quality, security reviews, delivery metrics, stakeholder collaboration, and vendor tools. Hires, mentors, and retains engineers while ensuring service-level commitments, innovation, cost effectiveness, and timely delivery.

Leads software engineering for Mastercard’s Payment Cancellation Service, overseeing application development, maintenance, architecture, reviews, security compliance, delivery metrics, and service-level performance. Manages engineering resources, collaborates with business and operations teams, shapes technology strategy, drives innovation, and hires, mentors, and retains engineering talent. The role requires hands-on technical leadership, strong software engineering knowledge, and effective communication and stakeholder collaboration.

Leads software engineering teams responsible for building, operating, and maintaining payment cancellation systems. Manages major projects, technical strategy, application resources, delivery metrics, stakeholder collaboration, architecture and code reviews, security compliance, and service-level commitments. The role also involves hiring, mentoring, retaining engineering talent, driving innovation, and ensuring high-quality, cost-effective delivery.

Leads software engineering teams responsible for building, operating, and maintaining payment cancellation services. Manages major projects, system development, architecture, code and security reviews, delivery metrics, and service-level objectives. Partners with stakeholders and vendors, defines technology strategies, drives innovation, and ensures quality and compliance. Hires, mentors, and retains engineers while fostering strong team culture and communicating objectives and success measures.

Leads a software engineering team responsible for developing, operating, and maintaining payment cancellation services. Manages major projects, technical strategy, application resources, delivery metrics, stakeholder collaboration, and vendor tools. Oversees architecture, design, code, security reviews, and quality inspections while ensuring compliance with service-level agreements and Mastercard standards. Builds, mentors, and retains engineering talent, drives innovation, and supports long-term business technology goals.

Leads a software engineering team responsible for developing, operating, and maintaining Mastercard’s Payment Cancellation Service. Oversees major projects, architecture, design, code, security, and quality reviews; establishes delivery metrics; collaborates with stakeholders and vendors; defines technology strategies; and hires, mentors, and retains engineering talent while meeting SLAs and business goals.

Leads software engineering teams responsible for building, operating, and maintaining payment cancellation services. Manages application development, system maintenance, architecture, design, code, security reviews, delivery metrics, stakeholder collaboration, technology strategy, and service-level commitments. The role also includes hiring, mentoring, retaining engineering talent, driving innovation, and ensuring solutions meet Mastercard quality, security, cost, and time-to-market standards.

Leads software engineering teams developing, operating, and maintaining payment cancellation systems. Oversees major projects, architecture, design, code, security reviews, SLAs, delivery metrics, technology strategy, stakeholder collaboration, and vendor tools. Hires, mentors, and retains engineers while fostering team culture. Ensures solutions are innovative, cost-effective, high quality, and delivered quickly in compliance with Mastercard standards.

Leads software engineering teams developing, operating, and maintaining payment cancellation services. Oversees major projects, architecture, design, code, security reviews, delivery metrics, stakeholder collaboration, technology strategy, and SLA performance. Hires, mentors, and retains engineers while driving innovation, quality, cost effectiveness, and timely delivery. Ensures compliance with Mastercard security standards and policies.

Leads a software engineering team responsible for building, operating, and maintaining payment cancellation services. Manages major projects, technical strategy, system development, service-level delivery, architecture and code reviews, security compliance, performance metrics, and vendor tools. Collaborates with business, operations, and program management stakeholders; hires, mentors, and retains engineers; and drives innovation, quality, cost effectiveness, and timely delivery.

Lead and build an AI-native engineering OS and developer experience: design model access, agent orchestration, prompt/spec frameworks, CI/CD integration, governance, cost optimization, and developer portals. Architect scalable, model-agnostic platforms, drive org-wide adoption, and manage a team of AI platform and developer-experience engineers while operating within compliance constraints (PCI, SOX).

Lead development of scalable scheduling software for Toast’s restaurant workforce management product. Responsibilities include full-stack feature development, solution design, estimation, testing, debugging, technical reviews, mentoring developers, and collaboration with product managers, designers, customer success, and engineering stakeholders. The role also champions software quality and development practices, contributes to product decisions, and uses AI tools to improve engineering productivity. This is a hybrid position requiring two days per week in the Dublin office.

Lead a Dublin engineering team owning the OLAP platform for real-time reporting and AI-driven products. Define technical strategy, scale platform performance and cost, build cross-team partnerships, implement monitoring and operating mechanisms, mentor engineers, and enable safe AI-first platform capabilities.

Lead a hands-on engineering team to design and deliver IoT and edge-to-cloud solutions that integrate AI/ML for real-time workplace insights. Architect resilient, secure pipelines, enforce data governance (FAIR), drive agentic AI adoption across the SDLC, mentor engineering talent, and split time between strategic leadership and active coding.