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AI Engineer

McGregor Boyall
Manchester, United Kingdom
Today
£800 pa

Salary

£800 pa

Posted
7 Sep 2026 (Today)
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AI Engineer – Enterprise Knowledge Base (EKB)
Role Overview
We are looking for an experiencedAI Engineer to design, build, and deploy enterprise-grade AI solutions that enhance knowledge discovery, retrieval, and automation. The ideal candidate will have strong expertise inGenerative AI,Large Language Models (LLMs), AI Agents, and modern AI application frameworks, with a passion for delivering scalable, production-ready solutions.
Key Responsibilities
  • Design and develop AI-powered applications usingGenAI, LLMs,NLP, andAgentic AI technologies.
  • Build intelligentRAG (Retrieval-Augmented Generation) solutions leveragingEmbeddings andVector Databases.
  • Develop and orchestrateAI Agents andMulti-Agent Systems to automate complex business workflows.
  • ApplyPrompt Engineering andContext Engineering techniques to optimise AI performance and accuracy.
  • Implement AI solutions using frameworks such asLangChain, LangGraph, andMCP.
  • Integrate AI services and enterprise platforms throughREST APIs and cloud-native architectures.
  • Deliver scalable, secure, and reliable solutions usingPython,SQL,Git, andCI/CD practices.
  • Test, evaluate, and continuously improveLLM andAI Agent performance, reliability, and safety.
  • Collaborate with business, data, and engineering teams to drive AI adoption and innovation.
Required Skills
  • AI,Generative AI (GenAI),Large Language Models (LLMs),Natural Language Processing (NLP)
  • Prompt Engineering,Context Engineering
  • AI Agents,Agentic AI,Multi-Agent Systems
  • LangChain,LangGraph,Model Context Protocol (MCP)
  • RAG,Embeddings,Vector Databases
  • Python,SQL,REST APIs
  • Git,CI/CD
  • Cloud Platforms (Azure, AWS, or GCP)
  • LLM & AI Agent Testing and Evaluation
Desirable Skills
  • Knowledge Graphs
  • Semantic Search
  • Responsible AI
  • Token Optimisation & Cost Management
  • AI Evaluations (Evals)
  • Re-ranking Techniques
  • Caching Strategies
Preferred Experience
  • Experience designing and implementingEnterprise Knowledge Bases (EKBs), AI-powered enterprise search, knowledge management, or intelligent retrieval platforms.
  • Experience delivering AI solutions from prototyping through to production deployment in enterprise environments.

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