Lead AI/ML Architect (GenAI, RAG, LLMs) – Hybrid Dublin

Stelfox IT Recruitment; Dublin; Hybride; EUR 148 000 - 203 000; Plein temps

Résumé du poste

Stelfox IT Recruitment is seeking a Lead AI Machine Learning Engineer for a Dublin-based, hybrid daily rate contract. The role focuses on leading the design and delivery of enterprise AI solutions using generative AI, LLMs, and RAG, with emphasis on scalable architectures and responsible AI.

You will mentor engineers, collaborate with Data Science, MLOps and API teams, and ensure robust testing, governance and deployment standards across enterprise applications.

Qualifications

• 7+ years hands-on AI/ML experience.
• Strong production experience with Generative AI and LLM‑based apps.
• Experience designing RAG architectures and AI agents/workflows.
• Proficiency with Python; JavaScript/TypeScript advantageous.

Responsabilités

• Lead architecture and implementation of enterprise AI solutions using LLMs, RAG and agentic AI.
• Design scalable AI architectures incorporating vector databases, APIs and modern AI frameworks.
• Build sophisticated RAG solutions with retrieval, context management and response generation.
• Develop AI agents and multi-step workflows capable of reasoning and tool use.
• Mentor engineers and provide technical direction across internal and third-party AI initiatives.

Connaissances

AI/ML expertise

Python

Leadership

Stakeholder comms

Prompt engineering

LLM evaluation

Context management

Model optimization

Guardrails

Cloud AWS

Formation

Bachelor's in CS/AI

Master's in CS/AI

Outils

Docker

Kubernetes

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Pinecone

Weaviate

Qdrant

MLOps

Description du poste

Stelfox IT Recruitment is seeking a Lead AI Machine Learning Engineer for a Dublin-based, hybrid daily rate contract. The role focuses on leading the design and delivery of enterprise AI solutions using generative AI, LLMs, and RAG, with emphasis on scalable architectures and responsible AI.

You will mentor engineers, collaborate with Data Science, MLOps and API teams, and ensure robust testing, governance and deployment standards across enterprise applications.