AI Technical Lead

Cpl; Dublin; Hybrid; EUR 111,000 - 120,000; Full time

Job summary

Cpl in Ireland is seeking an AI Technical Lead to drive enterprise AI capabilities. You will architect and implement LLM-based solutions, build RAG systems, and lead cross-functional teams to deliver measurable business value across financial services applications.

The role focuses on responsible AI, SDLC governance, and delivering high-impact AI-enabled workflows with modern frameworks and tools.

Qualifications

• 5+ years hands-on ML/AI experience.
• Proven production LLM applications experience.
• Designing RAG systems with vector retrieval.
• Agentic AI workflows with tool use.
• Experience with prompt engineering best practices.

Responsibilities

• Design AI architectures using LLMs, vector DBs, and agentic frameworks.
• Lead AI strategy and architecture for enterprise systems.
• Develop RAG implementations for knowledge-intensive processes.
• Guide responsible AI practices and governance.

Skills

AI/ML expertise

Production LLM apps

RAG systems

Agentic AI workflows

Prompt engineering

LangChain/LangGraph

UI/API integration

Python

Docker/Kubernetes

MLOps

Education

Bachelor's or Master's in CS/AI

Tools

LangChain

Llama Index

Semantic Kernel

Pinecone/Weaviate/Qdrant

Job description

Overview

We are seeking an experienced AI Technical Lead to drive the implementation of advanced AI capabilities supporting our enterprise transformation programs. The ideal candidate will have deep expertise in modern AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI systems. This role will focus on leveraging cutting-edge AI frameworks to deliver business value through intelligent automation, enhanced user experiences, and optimized workflows in our financial services applications.

Contract & Salary

12 month Day Rate Contract

Dublin Hybrid - €600-€650 per day

About The Role

As an AI Technical Lead, you will be responsible for designing, implementing, and scaling AI solutions across our enterprise systems. You will work at the intersection of emerging AI technologies and practical business applications, guiding cross-functional teams in the adoption of responsible AI practices while ensuring technical excellence and innovation.

Primary Responsibilities AI Strategy & Architecture

• Design comprehensive AI architectures incorporating LLMs, vector databases, and agentic frameworks
• Establish patterns for effective AI integration with existing enterprise applications
• Develop robust RAG implementations for knowledge-intensive business processes
• Balance innovation with practical delivery of strategically agreed capabilities to ensure measurable business value

Technical Leadership in AI

• Lead the evaluation and selection of appropriate AI models, tools, and frameworks
• Design end-to-end AI workflows incorporating prompt engineering, context handling, and tool use
• Guide the responsible implementation of generative AI capabilities in businesscritical systems, project SDLC and system workflows
• Establish best practices for AI development, testing, and deployment

Advanced AI Implementation

• Develop LLM-powered applications with sophisticated reasoning capabilities
• Create RAG systems with effective vector retrieval, context management, and response generation
• Build agentic AI workflows that can perform multi-step tasks with appropriate tool use
• Implement AI-powered document intelligence and information extraction systems
• Design hybrid AI architectures combining symbolic and neural approaches where appropriate
• Develop generative AI solutions for intuitive UI creation and personalized user experiences

AI Technical Expertise

• Implement fine-tuning and model adaptation strategies for specialized domains
• Develop robust evaluation frameworks for AI system performance and reliability
• Create effective prompt engineering strategies for consistent and controlled AI outputs
• Design and implement AI guardrails and safety mechanisms for enterprise applications Team Leadership
• Mentor development teams in advanced AI implementation techniques
• Collaborate with data scientists, MLOps engineers, and business analysts
• Evangelize AI best practices and responsible AI principles across the organization
• Provide technical oversight for internal and vendor-provided AI solutions

Required Skills & Experience AI & ML Expertise

• 5+ years of hands-on experience with ML/AI technologies
• Demonstrated experience implementing production LLM applications
• Proven ability to design and develop RAG systems with effective vector retrieval
• Experience designing agentic AI workflows with tool-using capabilities
• Working knowledge of prompt engineering techniques and best practices
• Hands-on experience with LLM frameworks (LangChain, LangGraph, Llama Index, Semantic Kernel, etc.)
• Experience in full stack development is a plus, should be able to work with UI engineers and API leads to build UIs including conversation AI usecases
• Understanding of model fine-tuning, quantization, and optimization approaches Technical Foundation
• Strong software engineering background with proficiency in Python, JavaScript/TypeScript
• Experience with vector databases (Pinecone, Weaviate, Qdrant, etc.)
• Knowledge of modern AI development tools (GitHub Copilot, Claude/GPT APIs, Hugging Face)
• Experience with containerization and orchestration (Docker, Kubernetes)
• Understanding of MLOps practices for AI application deployment

Architecture & Integration

• Experience integrating AI capabilities into enterprise systems
• Knowledge of API development and microservices architecture
• Cloud platform experience (AWS)
• Understanding of event-driven architectures and messaging patterns
• Experience with observability and monitoring for AI systems

Leadership & Soft Skills

• Proven track record leading technical teams on innovative projects
• Excellent communication with technical and non-technical stakeholders
• Ability to translate business requirements into AI-enabled solutions
• Experience working in Agile/Scrum environments
• Problem-solving skills and innovative thinking

Qualifications

• Bachelor's or Master's degree in Computer Science, AI, or related field
• Relevant certifications in AI/ML beneficial
• Experience leading enterprise-scale AI implementation projects
• Demonstrated commitment to continuous learning in the rapidly evolving AI landscape