Senior Agentic AI Engineer

Job Summary

Senior Agentic AI Engineer – Leeds City Centre (permanent, hybrid: 2 days in office, 3 days remote).

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 across use cases such as developer productivity, knowledge retrieval, and process automation.
• Leverage GCP‑native and enterprise‑grade managed services rather than building custom infrastructure.
• Develop end‑to‑end RAG architectures (ingestion, chunking, embedding, retrieval, reranking).
• Select and manage appropriate vector databases and build pipelines to transform unstructured data into usable insights.
• Apply knowledge graph approaches (e.g., Neo4j) where deeper relational or semantic reasoning is needed.
• Define and implement evaluation frameworks, including automated testing and LLM‑based assessment.
• Monitor and optimise agents for cost, latency, quality, and production performance.
• Collaborate across engineering and business teams to build scalable, compliant (GDPR/EU AI Act) and production‑ready agentic solutions.

Qualifications

• Proven experience building and deploying agentic AI systems in production (not just prototypes).
• Strong Python engineering skills with a focus on clean, tested, maintainable code.
• Hands‑on experience designing RAG pipelines (chunking, embeddings, retrieval, evaluation).
• Experience working with at least one vector database in a production setting.
• Practical experience with LLM evaluation techniques (e.g., automated evals, LLM‑as‑a‑Judge).
• Familiarity with agent frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen) and judgement on their use.
• Solid understanding of LLM fundamentals: prompting, tool use, structured outputs, context management.
• Experience with cloud platforms (GCP preferred; AWS or Azure also considered).
• Desirable: Experience with Google Agent Development Kit (ADK) or Vertex AI Agent Builder.
• Understanding of MCP (Model Context Protocol) and agent‑to‑agent communication patterns.
• Experience with knowledge graphs or graph databases (e.g., Neo4j, JanusGraph).
• Familiarity with LLMOps and observability tools (e.g., LangSmith, Langfuse).
• Experience building solutions in regulated or enterprise environments.
• Background in BPO, AP automation, or document processing workflows.

Benefits

• Competitive salary + bonus.
• 25 days annual leave (plus 5 additional days that can be purchased).
• Birthday off and an extra 3 days of annual leave after 5 years of service.
• Well‑being and mental health benefits: Calm app, personal medical, critical illness cover, dental insurance.
• Matched pension contribution up to 10%.
• Car benefit scheme.
• Online learning platform for continuous development.

EEO Statement

Liberty Global is an equal opportunity employer, committed to an inclusive environment and accommodating all candidates.

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