Top AI & Machine Learning Jobs in Dublin

Design and deliver enterprise AI solutions using LLMs, RAG, and vector search. Build knowledge bases, scalable cloud-native services (AWS/Cloudera/Databricks), APIs/microservices, and production-grade model integrations. Monitor model performance, ensure security and compliance, mentor engineers, and collaborate cross-functionally to translate business needs into AI-enabled products.

Design, build, and deliver enterprise-grade AI solutions using LLMs, RAG, LangChain, and vector search. Architect secure, scalable cloud/data systems (AWS, Cloudera, Databricks), develop APIs and microservices, optimize model performance in production, and mentor engineers while ensuring governance, security, and compliance.

Design, develop, and deploy enterprise-grade AI solutions using LLMs, RAG, and vector-search knowledge bases. Build scalable, secure cloud-native systems (AWS, Cloudera, Databricks), APIs, and microservices; implement LangChain and MCP patterns; monitor and optimize production model performance; ensure data governance and compliance; mentor engineers and drive engineering best practices.

Lead engineering strategy and hands-on delivery for agentic AI products and platforms. Build and scale teams and reusable agent frameworks, drive architecture for production-grade LLM/agent systems (context, memory, tool integration, orchestration, observability, safety), partner with Product and Data Science, and establish engineering standards, tooling, and measurable success criteria to move experiments into governed, scalable production.

Lead and deliver production-grade agentic AI systems and platforms. Define engineering vision, build and scale teams, architect agent frameworks and orchestration, ensure security, observability, and governance, partner with Product and Data Science, and drive adoption of AI tooling and developer productivity across the organization.

Lead engineering teams to build and operate cloud-native API platforms exposing foundation model capabilities. Drive API and distributed-systems best practices, security, observability, CI/CD, and reliable production deployments. Partner with AI teams, manage delivery across workstreams, and hire, coach, and scale high-performing engineering talent.

Design, build, and deploy enterprise AI solutions using LLMs, RAG, and vector search. Architect scalable, secure cloud-based systems (AWS, Databricks, Cloudera), develop APIs and microservices, optimize model performance, and ensure data governance and compliance. Mentor engineers and collaborate cross-functionally to deliver production-ready 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 team building and operating API platforms and backend services that expose foundation model capabilities. Drive architecture, security-by-design, scalability, reliability, CI/CD, observability, and AI model integration. Manage multiple workstreams, hire and coach engineers, and translate product requirements into technical roadmaps.

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.