Top AI Jobs in Dublin

Leads the architecture, prototyping, engineering, and global deployment of immersive Mastercard Experience Centre technologies. Designs reusable frameworks for AI demonstrations, mixed reality, spatial computing, interactive installations, visualization, IoT environments, and production systems. Owns delivery from concept through deployment, establishes technical standards and support models, and leads cross-functional teams and external partners. Engages executives and customers to translate business needs into compelling, reliable technology experiences while mentoring teams and driving adoption of emerging technologies.

Leads the architecture, prototyping, engineering, and global deployment of immersive Mastercard Experience Centre technologies. Designs reusable frameworks and production systems for AI, mixed reality, spatial computing, interactive installations, visualization, IoT, and executive demonstrations. Oversees technical strategy, delivery, integrations, operational support, and global rollout while partnering with product, engineering, creative, security, vendors, and senior stakeholders. Translates customer and business needs into scalable, reliable, and compelling technology experiences.

Lead go-to-market strategy and execution for AI-led Built On ServiceNow solutions with strategic service provider partners. Develop partner GTM plans, drive sales and pipeline growth, coordinate field engagement, enablement, marketing assets, events, and communications, and track initiative performance. Collaborate cross-functionally with sales, marketing, product management, industry GTM, and account teams to support business development, proposals, pipeline conversion, and partner revenue targets.

Own the strategy, roadmap, discovery, experimentation, and measurable outcomes for a strategic employee recognition product domain. Partner with Engineering, Design, Marketing, Customer Excellence, and senior leaders to deliver scalable, intuitive, AI-powered B2B SaaS experiences. Clarify requirements, prioritize work, support sprint execution, use customer and product data to guide decisions, and mentor junior product professionals.

Leads complex, strategic projects from initiation through implementation for Payment Integrity’s transformation agenda. Defines scope, milestones, governance, metrics, and execution plans; coordinates cross-functional dependencies; manages risks and roadblocks; aligns stakeholders; supports executive decision-making through clear reporting; and improves project delivery processes. The role partners across operations, technology, product, finance, compliance, and strategy, while leveraging AI and digital automation to improve execution and business outcomes.

Manages the Coordination of Benefits and Ideation & Growth portfolios, leading opportunity prioritization, forecasting, executive reporting, KPI tracking, value realization, and productivity planning. Drives modernization through AI, machine learning, automation, improved data integration, and scalable operating models. Partners with Operations, Finance, Product, Technology, Analytics, Data Science, and leadership teams to develop business cases, deploy innovation, monitor savings and revenue, and improve operational efficiency and growth outcomes.

Leads enterprise product security across Google Cloud, AWS, AI applications, and software development. Designs security solutions, develops threat-modeling frameworks, conducts code reviews and vulnerability testing, integrates secure practices into the SDLC, and creates security policies. Triages threats, assesses risks, manages corrective actions, communicates findings to technical and executive stakeholders, and validates AI-assisted security recommendations for security, resiliency, data protection, and auditability.

Lead strategic product domains for Mastercard's next-generation disputes platform, define roadmaps, prioritize investments, and scale AI-enabled capabilities across engineering, data science, and design teams to improve dispute resolution, automation, and customer outcomes.

Lead product strategy and execution for Mastercard's next-generation disputes platform. Define domain vision, prioritize roadmaps, drive AI-enabled automation and predictive decisioning, partner with engineering, data science, and stakeholders, and influence executive investment to scale platform capabilities and improve customer and operational outcomes.

Leads the design, development, deployment, and evaluation of machine learning solutions, including forecasting, recommendation, propensity, fraud, and customer analytics models. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, and partners with product, engineering, analytics, and business teams. Mentors data scientists and AI engineers, presents technical recommendations to leadership, supports hiring, and shapes the organization’s long-term technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, embeddings, and foundation-model applications. Defines experimentation frameworks and success metrics, measures business impact, partners with cross-functional stakeholders, presents findings to leadership, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the technical direction of the AI organization.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the long-term technical direction of the AI organization.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendation systems, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model representations, measures business impact, and partners with cross-functional stakeholders. Mentors data scientists and AI engineers, presents recommendations to leadership, contributes to hiring, and helps shape the organization’s technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendation systems, fraud detection, and customer analytics. Defines experimentation frameworks, applies embeddings and foundation models, measures business impact, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. Contributes to hiring, capability development, and the long-term technical direction of the AI organization.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendations, forecasting, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, partners across functions, presents technical recommendations, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the AI organization’s technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions for forecasting, recommendations, propensity modeling, fraud detection, and customer analytics. Defines modeling and experimentation strategies, applies foundation-model embeddings, measures business impact, partners with cross-functional stakeholders, and mentors data scientists and AI engineers. The role also contributes to technical direction, hiring, and capability development.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, embeddings, and foundation-model applications. Defines experimentation frameworks, metrics, and technical direction while partnering with business, product, engineering, and analytics teams. Presents insights to senior stakeholders, mentors data scientists and AI engineers, and drives projects from problem definition through measurable business impact and production deployment.

Lead machine learning and data science initiatives from problem definition through production deployment and business impact measurement. Develop predictive models, recommendation systems, forecasting, fraud detection, and customer analytics solutions using modern machine learning and foundation-model techniques. Establish experimentation and evaluation frameworks, partner with cross-functional stakeholders, present technical recommendations, mentor data scientists and AI engineers, and shape the organization’s technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendations, fraud detection, embeddings, and foundation-model applications. Defines experimentation frameworks and success metrics, drives projects from conception through production, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. Contributes to hiring, capability development, and the organization’s long-term technical direction.

Leads the design, development, deployment, and evaluation of advanced machine learning solutions, including forecasting, recommendation, propensity, fraud, and customer analytics models. Defines experimentation frameworks, applies embeddings and foundation-model techniques, measures business impact, and partners with business, product, engineering, and analytics teams. Mentors data scientists and AI engineers, influences technical direction, presents findings to leadership, and contributes to hiring and capability development.

Coordinates multi-country EMEA labor relations projects, tracking timelines, reporting, data integrity, dashboards, and stakeholder alignment. Develops scalable templates, playbooks, intake processes, leadership briefings, and operational workflows. Partners with Employee Success teams on process improvement, standardization, AI-powered automation, and Slack-based tooling. The role emphasizes operational rigor, documentation, continuous improvement, systems thinking, and clear written communication.

Designs, develops, deploys, and supports secure enterprise applications, integrations, and AI-enabled solutions. Responsibilities include full software development lifecycle ownership, AI and LLM integration, relational database design, API development, data architecture, cloud-hosted solutions, production troubleshooting, and continuous improvement. Provides technical leadership, mentors developers, collaborates with stakeholders, and ensures applications are scalable, maintainable, secure, and aligned with business objectives.

Own the full sales cycle for startup customers across EMEA, from outbound prospecting through launch. Drive revenue and quota attainment through consultative, technical sales of Anthropic’s AI solutions. Develop market-expansion strategies, identify customer segments and use cases, negotiate complex agreements, gather feedback to inform product roadmaps, and help establish regional go-to-market processes, playbooks, and sales methodologies.

Graduate engineering opportunities across Analog Devices’ Ireland locations in electronics, semiconductor, software, AI, robotics, manufacturing, research, quality, and supply chain. Graduates may work in IC design, embedded software, verification, RF design, process engineering, testing, packaging, reliability, and related functions. The program includes rotations, learning opportunities, relocation assistance, and access to advanced facilities. Recruitment begins in September 2026 on a rolling basis. No travel is required.

Graduate software engineering opportunities involving embedded software, software systems, software development, AI, machine learning, UI/UX design, and cloud architecture. Graduates collaborate with hardware teams on planning, system architecture, development, troubleshooting, debugging, and testing across applications including IoT, automotive radar, healthcare monitoring, and 5G. The role includes a graduate rotation program, learning opportunities, and exposure to advanced semiconductor technologies.