1 to 25 of 123 Retrieval-Augmented Generation Jobs in the UK

experience working with large language models (LLMs), prompt engineering, and frameworks like LangChain, with knowledge of advanced patterns such as Retrieval-Augmented Generation (RAG) and agent-based systems. A strong foundation in Agile SDLC practices is essential, along with familiarity in containerization, DevOps, and low-code/no-code platforms. Experience across both backend … enable scalable, interoperable systems. Frameworks & Tools: Backend: Spring Boot (web, data, cloud, security), JUnit 5, Mockito, database integration. AI: LangChain, Retrieval-Augmented Generation (RAG), MCP servers (as consumer and developer), and prompt engineering for LLM optimization. Exposure to popular libraries and frameworks (Apache Commons, Guava, Swagger, TestContainers). Architecture & Platforms: Skilled in designing and … and model safety considerations. AI Development: End-to-end development of AI-powered solutions, from concept to production readiness. Practical experience with LLMs and agentic AI, including LangChain integration, RAG pipelines, prompt engineering, and model consumption via APIs. Ability to bridge backend and AI workflows, integrating advanced AI capabilities into scalable enterprise platforms. SDLC & Agile Practices: Familiar with the Software More ❯

experience working with large language models (LLMs), prompt engineering, and frameworks like LangChain, with knowledge of advanced patterns such as Retrieval-Augmented Generation (RAG) and agent-based systems. A strong foundation in Agile SDLC practices is essential, along with familiarity in containerization, DevOps, and low-code/no-code platforms. Experience across both backend … enable scalable, interoperable systems. Frameworks & Tools:Backend: Spring Boot (web, data, cloud, security), JUnit 5, Mockito, database integration. AI: LangChain, Retrieval-Augmented Generation (RAG), MCP servers (as consumer and developer), and prompt engineering for LLM optimization. Exposure to popular libraries and frameworks (Apache Commons, Guava, Swagger, TestContainers). Architecture & Platforms:Skilled in designing and … and model safety considerations. AI Development: End-to-end development of AI-powered solutions, from concept to production readiness. Practical experience with LLMs and agentic AI, including LangChain integration, RAG pipelines, prompt engineering, and model consumption via APIs. Ability to bridge backend and AI workflows, integrating advanced AI capabilities into scalable enterprise platforms. SDLC & Agile Practices: Familiar with the Software More ❯

experience working with large language models (LLMs), prompt engineering, and frameworks like LangChain, with knowledge of advanced patterns such as Retrieval-Augmented Generation (RAG) and agent-based systems. A strong foundation in Agile SDLC practices is essential, along with familiarity in containerization, DevOps, and low-code/no-code platforms. Experience across both backend … enable scalable, interoperable systems. Frameworks & Tools: Backend: Spring Boot (web, data, cloud, security), JUnit 5, Mockito, database integration. AI: LangChain, Retrieval-Augmented Generation (RAG), MCP servers (as consumer and developer), and prompt engineering for LLM optimization. Exposure to popular libraries and frameworks (Apache Commons, Guava, Swagger, TestContainers). Architecture & Platforms: Skilled in designing and … and model safety considerations. AI Development: End-to-end development of AI-powered solutions, from concept to production readiness. Practical experience with LLMs and agentic AI, including LangChain integration, RAG pipelines, prompt engineering, and model consumption via APIs. Ability to bridge backend and AI workflows, integrating advanced AI capabilities into scalable enterprise platforms. SDLC & Agile Practices: Familiar with the Software More ❯

ensuring robust versioning, monitoring, and adherence to best practices. Drive the integration of external knowledge bases and retrieval systems to augment LLM capabilities. Research and Development: Effective RAG architectures and technologies for organizing complex domain-specific data (e.g. vector databases, knowledge graphs) and effective knowledge extraction. Explore and benchmark state-of-the-art LLMs, tuning, adaptation, and training … technical projects to successful completion in agile environments. Strong communication skills to align technical solutions with business goals. Ability to mentor and foster innovation within the team. LLM and RAG Expertise: Strong expertise in building Retrieval-Augmented Generation (RAG) architectures and integrating with vector and graph databases. Transformer and LLM Architectures: In-depth experience More ❯

collaborate with data scientists, ML engineers, and analysts to design and implement solutions that extract insights from unstructured text. Projects may include topic modelling and entity recognition, text generation, ontology creation, and conversational AI. This role demands strong technical expertise in NLP and a passion for innovation and problem-solving. This is a hybrid role based in our … free to ask us about the access to work scheme. Desirable Skills Experience using Azure OpenAI and foundational LLMs for Retrieval-Augmented Generation (RAG), including open-source implementations. Experience with LLM architecture (e.g., Transformer, GANs, VAEs), Fine-tuning PEFT/LoRA, Context embedding, Vector database technologies, and Semantic Search techniques & tools. Familiarity with Azure More ❯

of the experience listed below, please apply. Your Impact at Lila We are seeking a Senior Backend Engineer to join our software group and help build the next generation AI-driven scientific platform. In this role, you will design, build, and optimize backend systems that power intelligent, data-driven applications. You will focus on creating high-performance APIs … maintainability. Bonus Points For Hands-On with Latest AI Tools: Exposure to AI technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or agentic frameworks, as well as experience leveraging AI to improve development performance. Scientific or Data-Intensive Domains: Experience working with life sciences, material sciences, or other research-heavy fields. More ❯

projects, driving timelines, and delivering high-quality results in fast-paced environments. Bonus Experience in deploying multi-agent frameworks and retrieval-augmented generation (RAG) pipelines. Familiarity with regulatory and privacy considerations in healthcare AI applications. IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences More ❯

ML algorithms : regression, classification, clustering, and deep learning. Hands-on experience with Large Language Models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG) , agent orchestration , prompt engineering , and tool calling . Familiarity with AI standards like Model Context Protocol (MCP) and Agent2Agent (A2A) . Experience with automated testing and validation of AI outputs. More ❯

with a focus on leveraging AI/GAI technologies and large language models (LLMs) Advanced AI Integration : Apply experience with retrieval-augmented generation (RAG), vector databases (e.g. Pinecone, Weaviate, FAISS), and enterprise search for AI-driven knowledge discovery Optimize AI Performance : Utilize practical experience designing structured prompts, fine-tuning models, and cost optimization strategies More ❯

SQL, and other relevant languages. Ability to build AI-driven solutions using large language models (LLMs), and techniques such as retrieval-augmented generation (RAG) and agent-based approaches, supported by frameworks like LangChain and CrewAI. Skilled in leveraging AI model APIs (e.g. OpenAI, Anthropic) and rapid prototyping tools such as Streamlit, along with AI More ❯

SQL, and other relevant languages. Ability to build AI-driven solutions using large language models (LLMs), and techniques such as retrieval-augmented generation (RAG) and agent-based approaches, supported by frameworks like LangChain and CrewAI. Skilled in leveraging AI model APIs (e.g. OpenAI, Anthropic) and rapid prototyping tools such as Streamlit, along with AI More ❯

Cloud Expertise: Hands-on experience with Large Language Models (LLMs) and understanding of performance vs. cost trade-offs Familiarity with Retrieval-Augmented Generation (RAG) , agent orchestration, prompt engineering, and tool calling Knowledge of AI standards like Model Context Protocol (MCP) and Agent2Agent (A2A) Strong grasp of ML algorithms: regression, classification, clustering, deep learning Awareness More ❯

SQL, and other relevant languages. Ability to build AI-driven solutions using large language models (LLMs), and techniques such as retrieval-augmented generation (RAG) and agent-based approaches, supported by frameworks like LangChain and CrewAI. Skilled in leveraging AI model APIs (e.g. OpenAI, Anthropic) and rapid prototyping tools such as Streamlit, along with AI More ❯

SQL, and other relevant languages. Ability to build AI-driven solutions using large language models (LLMs), and techniques such as retrieval-augmented generation (RAG) and agent-based approaches, supported by frameworks like LangChain and CrewAI. Skilled in leveraging AI model APIs (e.g. OpenAI, Anthropic) and rapid prototyping tools such as Streamlit, along with AI More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯