Top AI & Machine Learning Jobs in Dublin

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.

Lead the design, development, and production deployment of AI-powered products, intelligent agents, and cloud-native analytics platforms. Architect agentic systems with reasoning, memory, retrieval, evaluation, safety, and human-in-the-loop controls. Build scalable services, APIs, and data applications using AWS, Azure, Databricks, Spark, Python, and Java. Drive architecture reviews, engineering excellence, CI/CD, DevSecOps, technical execution, modernization, and mentorship across globally distributed teams.

Lead the architecture and development of scalable, cloud-native AI products, intelligent agents, agentic workflows, and analytics platforms. Design production-grade systems using LLMs, retrieval, orchestration, memory, evaluation, and safety controls. Build APIs and distributed services with Python, Java, AWS, Azure, Databricks, and Spark. Drive technical execution, architecture reviews, DevSecOps, automation, reliability, governance, and mentoring across globally distributed engineering teams.

Build and lead scalable full-stack, data-intensive applications using distributed systems, cloud technologies, Databricks, Spark, and AI agentic workflows. Responsibilities include system design, API and data architecture, performance optimization, troubleshooting, secure coding, testing, observability, CI/CD, production readiness, cross-functional collaboration, and mentoring engineers.

Lead design and deliver enterprise AI solutions using LLMs, RAG, and vector search. Build knowledge bases, APIs, and scalable cloud-native systems (AWS, Cloudera, Databricks). Mentor engineers, ensure security/compliance, optimize model performance, and collaborate cross-functionally to productionize AI applications.

Lead design and deliver enterprise AI solutions using LLMs, RAG, and vector-search knowledge bases. Build scalable, secure cloud-native services and APIs, optimize model performance in production, mentor engineers, and enforce data governance and compliance.

Lead engineering and deliver production-grade AI solutions using LLMs, RAG, and vector-search knowledge bases. Architect scalable cloud solutions (AWS, Cloudera, Databricks), build APIs and microservices, implement MCP-style orchestration, monitor model performance, ensure security and compliance, and mentor engineering teams.

Lead design and deliver enterprise-grade AI solutions using LLMs, RAG, LangChain and vector search. Build and maintain knowledge bases, architect scalable cloud solutions (AWS, Cloudera, Databricks), develop APIs/microservices, ensure security/compliance, monitor model performance, mentor engineers, and collaborate cross-functionally to translate business needs into production AI systems.

Lead design and deliver enterprise AI solutions using LLMs, RAG, and vector search. Build knowledge bases, LLM-driven apps (LangChain), secure cloud/databricks integrations, APIs/microservices, monitor model performance, and mentor engineers while ensuring compliance and operational excellence.