Top Tech Jobs & Startup Jobs in Dublin

Leads hands-on development of AI and agentic platform capabilities, including LLM integrations, orchestration layers, knowledge bases, APIs, workflows, and data pipelines. Translates architecture and product priorities into scalable production solutions, guides engineers and vendors, reviews designs and code, mentors junior staff, and ensures security, privacy, reliability, compliance, and operational excellence. Partners across product, business, data, architecture, and engineering teams to deliver reusable AI capabilities and support consulting transformation.

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.

Develop and maintain secure, scalable backend services, RESTful APIs, and integrations supporting data, analytics, and AI-enabled capabilities. Collaborate with product, architecture, data engineering, and data science teams to deliver production-ready solutions. Responsibilities include software design, coding, testing, code reviews, CI/CD automation, troubleshooting, root cause analysis, observability, secure coding, and production support.

Designs, develops, tests, and maintains backend services, RESTful APIs, and integration components. Builds secure and scalable solutions, collaborates with product, architecture, data engineering, and data science teams, and supports CI/CD, automation, monitoring, production troubleshooting, and root cause analysis. The role contributes to software quality, reliability, secure coding, and continuous engineering improvements.

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.

Design, develop, test, and maintain backend services, RESTful APIs, and integration components. Collaborate with product, architecture, data engineering, and data science teams to deliver secure, scalable solutions. Participate in code reviews, CI/CD, production support, troubleshooting, root cause analysis, monitoring, automation, and reliability improvements while following security, privacy, and compliance standards.

Design, develop, test, and maintain backend services, RESTful APIs, and integration components. Build secure and scalable solutions, collaborate with product, architecture, data engineering, and data science teams, and support CI/CD, monitoring, troubleshooting, production reliability, and continuous improvement. Apply secure coding, privacy, compliance, and operational readiness practices throughout the software lifecycle.

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.