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.