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.

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