Senior Engineer, Applied AI

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.

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• Design, build and operate end‑to‑end production‑grade AI agent systems.
  
• Develop stateful agent workflows with checkpointing, retries and human‑in‑the‑loop controls.
  
• Architect intelligent agents with planning, tool use, memory and escalation strategies.
  
• Implement advanced retrieval pipelines, including hybrid search, reranking and context construction.
  
• Build robust evaluation frameworks with datasets, regression testing and clear success metrics.
  
• Establish LLMOps / AgentOps practices, including observability across cost, latency, drift and failures.
  
• Optimise system performance across latency, cost and output quality (e.g. routing, caching, model selection).
  
• Develop scalable backend services using Python (e.g. FastAPI) and modern architectures.
  
• Deploy and maintain systems using Docker, Kubernetes and CI/CD pipelines.
  
• Translate business requirements into scalable, production‑ready AI solutions.
  

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• Minimum of 4 years of experience in software engineering, applied machine learning or applied AI.
  
• Strong Python skills, with a solid grounding in modern engineering practices e.g. testing, code quality, version control.
  
• Demonstrated experience developing and deploying LLM‑powered applications, including prompt design, evaluation and productionisation.
  
• Practical experience with agent frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI or Langfuse.
  
• Hands‑on experience with retrieval systems and vector databases (e.g. Milvus, Pinecone, Weaviate, Chroma, FAISS).
  
• Good understanding of AI architecture patterns, including microservices, event‑driven systems and multi‑agent frameworks.
  
• Experience deploying applications on AWS, Azure or GCP using containerisation and CI/CD pipelines.
  
• Strong production mindset, with experience in monitoring, testing, governance and LLMOps practices. xcfaprz
  
• Exposure to developer copilots and rapid prototyping tools (e.g. Cursor, Windsurf, Replit, GitHub Copilot, Claude Code) is a plus.