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Our client, a growing Digital Transformation Consulting organisation, is hiring a hands-on Senior Applied AI Engineer to join the team in Dublin, Ireland on a contract basis. The successful candidate will design, build and scale advanced Generative and Agentic AI systems, contributing to the development of production-ready agent workflows, sophisticated retrieval pipelines, robust evaluation frameworks and scalable backend services.
Responsibilities-
Design, build and operate end-to-end production-grade AI agent systems.
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Develop stateful agent workflows with checkpointing, retries and human-in-the-loop controls.
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Architect intelligent agents with planning, tool use, memory and escalation strategies.
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Implement advanced retrieval pipelines, including hybrid search, reranking and context construction.
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Build robust evaluation frameworks with datasets, regression testing and clear success metrics.
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Establish LLMOps / AgentOps practices, including observability across cost, latency, drift and failures.
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Optimise system performance across latency, cost and output quality (e.g. routing, caching, model selection).
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Develop scalable backend services using Python (e.g. FastAPI) and modern architectures.
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Deploy and maintain systems using Docker, Kubernetes and CI/CD pipelines.
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Translate business requirements into scalable, production-ready AI solutions.
Skillset-
Minimum of 4 years of experience in software engineering, applied machine learning or applied AI.
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Strong Python skills, with a solid grounding in modern engineering practices e.g. testing, code quality, version control.
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Demonstrated experience developing and deploying LLM-powered applications, including prompt design, evaluation and productionisation .
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Practical experience with agent frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI or Langfuse.
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Hands-on experience with retrieval systems and vector databases (e.g. Milvus, Pinecone, Weaviate, Chroma, FAISS).
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Good understanding of AI architecture patterns, including microservices, event-driven systems and multi-agent frameworks.
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Experience deploying applications on AWS, Azure or GCP using containerisation and CI/CD pipelines .
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Strong production mindset, with experience in monitoring, testing, governance and LLMOps practices.
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Exposure to developer copilots and rapid prototyping tools (e.g. Cursor, Windsurf, Replit, GitHub Copilot, Claude Code) is a plus.
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