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.

Responsibilities

• 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.

Skillset

• 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.
• Exposure to developer copilots and rapid prototyping tools (e.g. Cursor, Windsurf, Replit, GitHub Copilot, Claude Code) is a plus.