26 to 50 of 241 Retrieval-Augmented Generation Jobs in England

innovation and deliver impactful solutions. Key Responsibilities: - Data & Retrieval: Build ingestion pipelines for structured and unstructured data; design retrieval-augmented generation (RAG) systems; manage vector and keyword indexes; develop NLP and recommendation systems; implement metadata and tagging frameworks. - LLM & ML Applications: Develop and maintain ML and LLM models; build LLM apps with … consumer-focused platforms is desirable. - Keen awareness of AI/ML industry trends and best practices. If you’re a hands-on AI engineer looking to shape next-generation research platforms, please send your CV and a brief introduction today. Important: This role does not offer visa sponsorship; applicants must have the right to work in the UK. More ❯

innovation and deliver impactful solutions. Key Responsibilities: - Data & Retrieval: Build ingestion pipelines for structured and unstructured data; design retrieval-augmented generation (RAG) systems; manage vector and keyword indexes; develop NLP and recommendation systems; implement metadata and tagging frameworks. - LLM & ML Applications: Develop and maintain ML and LLM models; build LLM apps with … consumer-focused platforms is desirable. - Keen awareness of AI/ML industry trends and best practices. If you’re a hands-on AI engineer looking to shape next-generation research platforms, please send your CV and a brief introduction today. Important: This role does not offer visa sponsorship; applicants must have the right to work in the UK. More ❯

Model Context Protocol for managing context and tool interfaces for agents. LLM integration patterns, including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of More ❯

Model Context Protocol for managing context and tool interfaces for agents. LLM integration patterns, including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of More ❯

Date: ASAP About the Opportunity: We are seeking a highly capable and intellectually curious Junior AI Engineer/Developer to join a fast-growing fintech company building next-generation AI infrastructure for financial services. This role is designed for a recent AI-focused Master’s graduate from a leading university who wants to move beyond academic models and … and capital-markets workflows into well-scoped AI problems and measurable targets Contributing to internal R&D on LLM evaluation, retrieval-augmented generation (RAG), and methods for improving reliability and explainability of models in financial contexts What We’re Looking For: A recently completed AI-focused Master’s degree from a top-tier university … tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using APIs, building simple RAG or prompt-based systems) is highly advantageous Comfortable working in Linux-based development environments, using Git, testing, and basic CI practices A structured, “extended thinking” mindset: you enjoy breaking down More ❯

Date: ASAP About the Opportunity: We are seeking a highly capable and intellectually curious Junior AI Engineer/Developer to join a fast-growing fintech company building next-generation AI infrastructure for financial services. This role is designed for a recent AI-focused Master’s graduate from a leading university who wants to move beyond academic models and … and capital-markets workflows into well-scoped AI problems and measurable targets Contributing to internal R&D on LLM evaluation, retrieval-augmented generation (RAG), and methods for improving reliability and explainability of models in financial contexts What We’re Looking For: A recently completed AI-focused Master’s degree from a top-tier university … tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using APIs, building simple RAG or prompt-based systems) is highly advantageous Comfortable working in Linux-based development environments, using Git, testing, and basic CI practices A structured, “extended thinking” mindset: you enjoy breaking down More ❯

of OWASP Top 10 and a proactive approach to identifying and mitigating security vulnerabilities during development. Experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines, working with LLM APIs (AWS Bedrock, OpenAI, Azure OpenAI), and using frameworks like LangChain or LangGraph. Strong knowledge of SDLC principles, CI/CD pipelines, and modern engineering practices. More ❯

of OWASP Top 10 and a proactive approach to identifying and mitigating security vulnerabilities during development. Experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines, working with LLM APIs (AWS Bedrock, OpenAI, Azure OpenAI), and using frameworks like LangChain or LangGraph. Strong knowledge of SDLC principles, CI/CD pipelines, and modern engineering practices. More ❯

as advanced chatbots, summarization tools, document Q&A systems, and code assistants. Advanced Techniques: Apply sophisticated techniques like Prompt Engineering , Retrieval-Augmented Generation (RAG) , and context-aware pipelines to maximize model accuracy and relevance. Integration: Seamlessly integrate deployed AI models with existing enterprise systems, APIs, and data stores using back-end languages like Python … Data Engineering for Generative AI: Experience in preparing and curating diverse training datasets (structured/unstructured text, images, code). Deep knowledge of data preprocessing, tokenization, and embedding generation techniques. Hands-on experience working with Vector Databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Stakeholder & Strategic Partnership: Ability to partner effectively with business More ❯

as advanced chatbots, summarization tools, document Q&A systems, and code assistants. Advanced Techniques: Apply sophisticated techniques like Prompt Engineering , Retrieval-Augmented Generation (RAG) , and context-aware pipelines to maximize model accuracy and relevance. Integration: Seamlessly integrate deployed AI models with existing enterprise systems, APIs, and data stores using back-end languages like Python … Data Engineering for Generative AI: Experience in preparing and curating diverse training datasets (structured/unstructured text, images, code). Deep knowledge of data preprocessing, tokenization, and embedding generation techniques. Hands-on experience working with Vector Databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Stakeholder & Strategic Partnership: Ability to partner effectively with business More ❯

A leading multi-strategy investment firm is seeking a Senior AI Engineer to join a high-impact Applied AI team focused on building next-generation tools that enhance decision-making across the investment lifecycle. Operating at the intersection of finance and machine intelligence, the team is responsible for developing production-grade AI systems that empower portfolio managers, analysts … containerised environments (Docker, Kubernetes). Solid grasp of distributed systems, networking, and infrastructure-as-code practices. Familiarity with vector databases, retrieval-augmented generation (RAG), and LLM integration is a plus. Exposure to cloud platforms (AWS preferred) and messaging systems (Kafka, RabbitMQ) is advantageous. Strong communication skills and the ability to work across technical and More ❯

a remote-first team Willingness to travel occasionally for in-person collaboration or client work Nice to Have Experience with retrieval-augmented generation (RAG) or foundation models Exposure to NLP, recommendation systems, or time series forecasting Familiarity with streaming architectures and experimentation platforms Understanding of healthcare data standards (HIPAA, FHIR) Interest in ethical AI More ❯

a remote-first team Willingness to travel occasionally for in-person collaboration or client work Nice to Have Experience with retrieval-augmented generation (RAG) or foundation models Exposure to NLP, recommendation systems, or time series forecasting Familiarity with streaming architectures and experimentation platforms Understanding of healthcare data standards (HIPAA, FHIR) Interest in ethical AI More ❯

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

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

root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and communicate results across cross-functional teams. Define, implement, and monitor key performance metrics for AI-driven product More ❯

root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and communicate results across cross-functional teams. Define, implement, and monitor key performance metrics for AI-driven product More ❯

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

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

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

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

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

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

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

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