Top AI & Machine Learning Jobs in Dublin

Leads hands-on development of AI and agentic systems for Mastercard’s consulting-focused AI platform. Designs and delivers reusable services, integrations, APIs, workflows, data pipelines, knowledge-base capabilities, and orchestration layers. Provides technical direction, reviews code, mentors engineers, coordinates vendors, and ensures secure, scalable, reliable production solutions. Partners across product, business, architecture, data, and engineering teams to implement LLM, retrieval-augmented generation, and agent workflows while supporting migration, governance, FinOps, and responsible AI practices.

Lead hands-on development of secure, scalable AI and agentic platform capabilities. Responsibilities include integrating LLMs, AI services, workflow engines, knowledge bases, APIs, data pipelines, and orchestration layers; translating architecture into production solutions; leading technical delivery; reviewing code; mentoring engineers; coordinating vendors; and ensuring reliability, security, privacy, compliance, and scalability.

Leads hands-on development of AI and agentic systems for Mastercard’s consulting-focused AI platform. Designs and delivers scalable services, APIs, workflows, integrations, data pipelines, knowledge-base capabilities, and reusable AI patterns. Provides technical direction, reviews code, mentors engineers and vendors, supports migrations, and ensures production solutions meet security, privacy, reliability, compliance, and scalability standards. Partners across product, business, architecture, data, and engineering teams to deliver applied AI capabilities.

Lead hands-on development of secure, scalable AI and agentic platform capabilities. Design and integrate LLMs, AI services, workflows, knowledge bases, APIs, data pipelines, and orchestration layers. Translate architecture and product priorities into production solutions, guide engineers and vendors, review code, mentor junior staff, and ensure reliability, security, privacy, compliance, and cost effectiveness. Partner across product, business, data, architecture, and engineering teams to deliver reusable AI capabilities and support organizational transformation.

Lead the design and development of secure, scalable AI platforms and agentic systems for Mastercard’s consulting organization. Responsibilities include integrating LLMs, AI services, workflow engines, knowledge bases, vector search, and orchestration platforms; building APIs, services, data pipelines, and reusable agent workflows; translating architecture into production solutions; guiding engineers and vendors; reviewing code; mentoring team members; and ensuring reliability, security, privacy, compliance, and operational readiness.

Leads hands-on development of scalable AI and agentic platform capabilities, integrating LLMs, AI services, workflow engines, knowledge bases, and orchestration layers. Designs and delivers APIs, services, data pipelines, event-driven workflows, and reusable platform components. Provides technical direction, reviews code, mentors engineers, coordinates vendors, and ensures secure, reliable, compliant, production-ready solutions. Partners across product, engineering, architecture, business, and governance teams to execute AI transformation initiatives.

Leads hands-on development of AI and agentic systems, reusable platform services, integrations, workflows, data pipelines, and developer capabilities. Translates architecture and product priorities into secure, scalable production solutions; guides engineers and vendors; reviews designs and code; supports migrations; and partners across product, business, data, architecture, and engineering teams. The role also advances LLM, orchestration, knowledge-base, FinOps, TokenOps, governance, reliability, and responsible AI practices.

Leads hands-on development of AI and agentic platform capabilities, including LLM integrations, orchestration, workflows, APIs, data pipelines, and knowledge bases. Translates architecture and product priorities into secure, scalable solutions; guides engineers and vendors; conducts design and code reviews; mentors team members; and ensures reliability, privacy, security, compliance, and production readiness.

Leads hands-on development of AI and agentic systems for a scalable enterprise AI platform. Designs and delivers reusable services, integrations, workflows, APIs, data pipelines, knowledge-base capabilities, and orchestration layers. Provides technical direction, reviews code, mentors engineers and vendors, and partners across product, business, architecture, and engineering teams. Ensures production solutions meet security, privacy, compliance, reliability, scalability, and cost objectives.

Lead hands-on development of secure, scalable AI and agentic platform capabilities. Design and integrate LLMs, AI services, agent frameworks, workflow engines, knowledge bases, APIs, data pipelines, and orchestration layers. Translate architecture and product priorities into production-ready solutions, provide technical direction, review code, mentor engineers, coordinate vendors, and ensure reliability, security, privacy, compliance, and scalability. Support AI platform migration, reusable engineering patterns, FinOps, TokenOps, and commercialization of AI-enabled consulting solutions.