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Liberty Blume

Agentic AI Engineer

AI Application EngineeringPosted on Nov 9
Full-timeLeeds, UKNo salary listed

About the Job

Requirements

  • Proven experience building and deploying agentic AI systems in production, not just prototypes.
  • Strong Python engineering skills focused on clean, tested, maintainable code.
  • Hands-on experience designing retrieval-augmented generation pipelines, including chunking, embeddings, retrieval, and evaluation.
  • Experience working with at least one vector database in a production setting.
  • Practical experience with large language model evaluation techniques, such as automated evaluations or LLM-as-a-Judge.
  • Familiarity with agent frameworks such as LangChain, LangGraph, CrewAI, or AutoGen, and good judgment about when to use them.
  • Solid understanding of large language model fundamentals, including prompting, tool use, structured outputs, and context management.
  • Experience working with cloud platforms; Google Cloud Platform is preferred, with AWS or Azure also considered.

Responsibilities

  • Design and build multi-agent systems for autonomous reasoning, planning, and task execution.
  • Architect orchestration patterns including tool use, memory, reflection loops, and human-in-the-loop handoffs.
  • Deliver solutions for use cases such as developer productivity, knowledge retrieval, and process automation.
  • Use Google Cloud Platform-native and enterprise-grade managed services before building custom infrastructure.
  • Develop end-to-end retrieval-augmented generation architectures covering ingestion, chunking, embedding, retrieval, and reranking.
  • Select and manage appropriate vector databases and build pipelines that turn unstructured data into usable insights.
  • Apply knowledge graph approaches, such as Neo4j, where deeper relational or semantic reasoning is needed.
  • Define and implement evaluation frameworks, including automated testing and large language model-based assessment.
  • Monitor and optimize agents for cost, latency, quality, and production performance.
  • Collaborate across engineering and business teams to build scalable, compliant, production-ready agentic solutions that comply with GDPR and the EU AI Act.

Desired Qualifications

  • Experience with Google Agent Development Kit or Vertex AI Agent Builder.
  • Understanding of Model Context Protocol and agent-to-agent communication patterns.
  • Experience with knowledge graphs or graph databases such as Neo4j or JanusGraph.
  • Familiarity with large language model operations and observability tools such as LangSmith or Langfuse.
  • Experience building solutions in regulated or enterprise environments.
  • Background in business process outsourcing, accounts payable automation, or document processing workflows.

About the Company

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