Top AI & Machine Learning Jobs in Dublin

Develops production-ready agentic AI systems and scalable integrations using AI-first software engineering practices. Designs multi-agent workflows, evaluates AI models, applies emerging standards, and works across the full software development lifecycle. The role also includes developer advocacy through demos, workshops, thought leadership, and executive presentations, while mentoring engineers and advancing code quality, developer experience, and innovation.

Lead the architecture, development, and productionization of AI-powered products, intelligent agents, and cloud-native analytics platforms. Design agentic systems with reasoning, memory, retrieval, evaluation, safety, and human oversight. Build scalable services and APIs using AWS, Azure, Databricks, Spark, Python, and Java. Drive technical execution, architecture reviews, DevSecOps, testing, reliability, governance, and cost optimization while mentoring engineers and coordinating globally distributed teams.

Lead the architecture, development, and production deployment of AI-powered products, intelligent agents, and cloud-native analytics platforms. Build agentic workflows using LLMs, retrieval systems, orchestration, memory, evaluation, and safety controls. Develop scalable services and APIs with AWS, Azure, Databricks, Spark, Python, and Java. Drive engineering standards, CI/CD, security, observability, technical execution, architecture reviews, and mentorship across globally distributed teams.

Leads architecture and hands-on development of enterprise AI products, intelligent agents, agentic workflows, analytics platforms, and cloud-native services. Designs secure, scalable systems using LLMs, retrieval, orchestration, memory, evaluation, and safety controls. Guides productionization through reliability, observability, governance, CI/CD, testing, and cost optimization. Partners across engineering, product, data, security, and operations teams; coordinates global technical execution, drives design and code reviews, establishes reusable platforms, and mentors engineers.

Lead the architecture, development, and production deployment of AI-powered products, intelligent agents, and agentic workflows. Build scalable cloud-native services, APIs, analytics platforms, and distributed systems using AWS, Azure, Databricks, Spark, Python, and Java. Establish reliability, security, governance, observability, and cost-optimization practices while coordinating global engineering teams. Drive technical decisions, reviews, CI/CD, automated testing, modernization, reusable platforms, and mentorship across the engineering organization.

Leads the design, development, and productionization of AI-powered products, intelligent agents, and agentic workflows. Architects scalable cloud-native platforms using LLMs, retrieval systems, orchestration frameworks, and modern data technologies. Provides hands-on software engineering, drives architecture and code reviews, coordinates global technical execution, improves reliability and developer productivity through automation and DevSecOps, and mentors engineers while ensuring security, observability, governance, and performance.

Lead the design, development, and production deployment of AI-powered products, intelligent agents, and cloud-native analytics platforms. Responsibilities include architecting agentic AI systems, building scalable services and APIs, establishing reliability and security practices, leading technical execution across global teams, conducting design and code reviews, driving CI/CD and DevSecOps, mentoring engineers, and improving platform scalability, observability, and developer productivity.

Lead the design, development, and production deployment of AI-powered products, intelligent agents, and agentic workflows. Architect scalable cloud-native systems using LLMs, retrieval, orchestration, and modern data technologies. Drive architecture reviews, engineering excellence, security, observability, CI/CD, testing, and platform modernization while coordinating distributed teams and mentoring engineers.

Lead technical design and hands-on development of AI-powered products, intelligent agents, agentic workflows, scalable services, APIs, and analytics platforms. Drive architecture, productionization, security, observability, reliability, CI/CD, DevSecOps, and engineering excellence across globally distributed teams. Mentor engineers, lead technical decisions and reviews, and build reusable platforms using cloud, data, and modern AI technologies.

Lead hands-on development of scalable, cloud-native AI products, intelligent agents, and agentic workflows. Architect production AI systems with orchestration, reasoning, memory, grounding, evaluation, safety, observability, and governance. Build distributed services, APIs, analytics platforms, and developer productivity tools using AWS, Azure, Databricks, Spark, Python, and Java. Drive technical execution, architecture reviews, CI/CD, DevSecOps, engineering standards, cross-team alignment, and mentorship.