More jobs:
AI Engineer
Job in
Manchester, Greater Manchester, M9, England, UK
Listed on 2026-09-09
Listing for:
McGregor Recruitment
Full Time
position Listed on 2026-09-09
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, AI Reliability/ Performance Engineer, AI QA / Validation Engineer
Job Description & How to Apply Below
AI Engineer – Enterprise Knowledge Base (EKB) Role Overview
We are looking for an experienced AI Engineer to design, build, and deploy enterprise-grade AI solutions that enhance knowledge discovery, retrieval, and automation. The ideal candidate will have strong expertise in Generative AI
, Large Language Models (LLMs),
AI Agents
, and modern AI application frameworks, with a passion for delivering scalable, production-ready solutions.
- Design and develop AI-powered applications using GenAI
, LLMs
, NLP
, and Agentic AI technologies. - Build intelligent RAG (Retrieval-Augmented Generation) solutions leveraging Embeddings and Vector Databases
. - Develop and orchestrate AI Agents and Multi-Agent Systems to automate complex business workflows.
- Apply Prompt Engineering and Context Engineering techniques to optimise AI performance and accuracy.
- Implement AI solutions using frameworks such as Lang Chain
, Lang Graph
, and MCP
. - Integrate AI services and enterprise platforms through REST APIs and cloud-native architectures.
- Deliver scalable, secure, and reliable solutions using Python
, SQL
, Git
, and CI/CD practices. - Test, evaluate, and continuously improve LLM and AI Agent performance, reliability, and safety.
- Collaborate with business, data, and engineering teams to drive AI adoption and innovation.
- AI
, Generative AI (GenAI),
Large Language Models (LLMs),
Natural Language Processing (NLP) - Prompt Engineering
, Context Engineering - AI Agents
, Agentic AI
, Multi-Agent Systems - Lang Chain
, Lang Graph
, 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
- Knowledge Graphs
- Semantic Search
- Responsible AI
- Token Optimisation & Cost Management
- AI Evaluations (Evals)
- Re-ranking Techniques
- Caching Strategies
- Experience designing and implementing Enterprise 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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