4 of 4 Permanent Information Retrieval Jobs in the UK excluding London

is a hands-on engineering position focused on building and operating production-grade LLM applications on Azure. You’ll work on AI-enabled and augmented intelligence solutions such as retrieval-augmented generation (RAG), agentic workflows, and model integrations with a strong emphasis on reliability, performance, security, and continuous improvement. Main Duties and Responsibilities Data & Retrieval Build robust ingestion … pipelines for PDFs/Word/Excel/Audio/JSON and semi-structured sources. Design RAG systems : chunking strategies, document schemas, metadata, hybrid/dense retrieval, re-ranking, and grounding. Manage vector/keyword indexes (e.g., Azure AI Search , pgvector, Pinecone/Weaviate). Develop and deploy advanced NLP, information retrieval, and recommendation systems that enhance More ❯

and help build the foundations of a generational product. The Role We're looking for an AI Engineer with deep experience in applied sub-fields such as recommender systems, retrieval-augmented generation (RAG), agentic AI, or automated decision-making to drive the development of our core product: Dragonfly's tool stack recommender engine. This role sits at the intersection … complex ideas simple and actionable. Shipping fast, learning faster, and iterating on user and stakeholder feedback. We Are Looking For Someone Who: Has hands-on experience with search and information retrieval, including BM25, hybrid search, and ranking metrics (nDCG, Reciprocal Rank, etc.). Understands recommender systems, from collaborative filtering to modern RAG pipelines. Knows how to design agentic More ❯

change and efficiency. Designs, builds, and deploys impactful AI and data-driven applications using cloud, data mesh, and knowledge base technologies such as centralized repositories, semantic search, and automated information retrieval systems that organize, store, and provide easy access to critical business data and insights. Integrates advanced analytics models and applications into operational workflows to ensure business value More ❯

the technical foundations for AI at Chambers, developing scalable solutions that push our technology forward and transform how we deliver value to our users. Main Duties and Responsibilities Data & Retrieval Build robust ingestion pipelines for PDFs/Word/Excel/Audio/JSON and semi-structured sources. Design RAG systems: chunking strategies, document schemas, metadata, hybrid/dense … retrieval, re-ranking, and grounding. Manage vector/keyword indexes (e.g., Azure AI Search, pgvector, Pinecone/Weaviate). Develop and deploy advanced NLP, information retrieval, and recommendation systems that enhance Chambers and Partners’ research and product offerings, including document understanding, automatic summarisation, topic modelling, semantic search, entity recognition, and relationship extraction. Design and implement intelligent tagging … knowledge graphs and tool routing. Cloud deployment & MLOps Production deployments on Azure (AKS/ACI/Functions), CI/CD, and Infrastructure as Code (Bicep/Terraform). Data & Information Management Experience with relational/semi-structured database (MS SQL and Cosmos DB) and vector search indexing (Azure AI Search/pgvec More ❯