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The Ardonagh Analytics Lab in Mullingar, Co. Westmeath, seeks an AI Engineer to design and operate production‑grade AI solutions, blending software engineering, data engineering and applied AI.
You will build AI agents, LLM‑powered apps and data pipelines using LLMs, RAG, MCP and MLOps in cloud environments. You’ll work with OpenAI, Azure OpenAI and similar platforms, shaping scalable AI architectures, performance and cost optimization across the analytics stack.
The Ardonagh Analytics Lab is a fast-growing centre of excellence within The Ardonagh Group, one of the world’s leading independent insurance distribution platforms. Based in Mullingar, Co. Westmeath, the Lab delivers data-driven insights to clients around the globe and supports more than 12,000 colleagues in providing tailored insurance solutions across a diverse range of products and services.
Our mission is to unlock the full value of data—building deeper understanding of risk, anticipating future outcomes, and empowering better decision‑making across the insurance value chain. As we expand our AI capabilities, we're looking for an innovative AI Engineer to help design and deliver the next generation of intelligent systems.
As an AI Engineer, you will play a pivotal role in designing, building and operating production‑grade AI solutions that transform data into actionable insight. You'll work at the intersection of software engineering, data engineering and applied AI, developing AI agents, LLM‑powered applications and intelligent data pipelines that solve real business challenges.
This is an exciting opportunity to work with cutting‑edge technologies including Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), Agentic AI, Model Context Protocol (MCP), MLOps/LLMOps, and cloud‑based AI services.
Design, build and maintain AI agents and agentic workflows that automate data processing, analysis and reporting.
Develop orchestration frameworks enabling tool use, reasoning and workflow automation.
Build intelligent solutions that drive efficiency and business value across the Analytics Lab.
Integrate and manage LLM APIs including OpenAI, Azure OpenAI, Anthropic Claude and similar platforms.
Design prompt frameworks, context management strategies and scalable AI architectures.
Optimise AI solutions for performance, reliability, latency and cost.
Design and maintain Retrieval‑Augmented Generation (RAG) solutions across proprietary datasets.
Build and operate vector databases and knowledge retrieval systems to deliver accurate, grounded AI outputs.
Develop AI‑powered data pipelines leveraging both structured and unstructured data sources.
Build and integrate Model Context Protocol (MCP) servers and tools.
Connect AI agents securely to internal systems, databases and third‑party platforms.
Ensure standardised, governed and scalable integrations across the AI ecosystem.
Create monitoring and evaluation frameworks to measure accuracy, latency, reliability and hallucination rates.
Implement responsible AI controls including guardrails, access controls, auditability and security measures.
Apply MLOps and LLMOps best practices including version control, CI/CD, testing and containerisation.
Partner with Data Scientists, Data Engineers and Platform Engineers to deliver integrated solutions.
Work with business stakeholders to identify opportunities for AI‑driven automation and innovation.
Contribute to technical documentation, architecture designs, evaluation reports and operational best practices.
Bachelor's degree in Computer Science, Data Science or a related discipline.
3+ years' experience in software engineering, data engineering or AI engineering roles.
Proven experience building and deploying AI, ML or LLM‑powered applications into production environments.
Strong Python development skills.
Experience integrating LLM platforms such as OpenAI, Azure OpenAI, Anthropic Claude or equivalent.
Hands‑on knowledge of frameworks including LangChain, LlamaIndex, LangGraph or similar.
Experience designing and operating RAG architectures and vector database solutions.
Understanding of Model Context Protocol (MCP) and integrating AI agents with enterprise systems.
Knowledge of MLOps/LLMOps practices and tools including Docker, CI/CD pipelines and model lifecycle management.
Experience with AI observability, evaluation frameworks and performance monitoring.
Familiarity with Azure AI services and cloud‑native AI deployments.
Strong understanding of AI governance, security, privacy and responsible AI principles.
Experience within Financial Services or General Insurance.
Exposure to enterprise‑scale data platforms and analytics environments.
An independent, technically strong problem solver who takes ownership and delivers high-quality solutions.
Passionate about emerging AI technologies and eager to explore innovative approaches that create measurable business value.
Able to translate complex business challenges into practical AI‑driven solutions.
A strong communicator who can engage confidently with technical and non‑technical stakeholders alike.
Collaborative, adaptable and comfortable working in an Agile environment.
This is a rare opportunity to help define how AI is applied across a global insurance organisation. You'll work on meaningful, real‑world challenges using the latest AI technologies within a highly skilled and forward‑thinking team.
If you're excited by AI agents, LLMs, RAG architectures and building intelligent systems that drive business impact, we'd love to hear from you.
Apply now and help us shape the future of AI‑powered insurance analytics.