1 to 25 of 65 Remote/Hybrid Retrieval-Augmented Generation Jobs in the UK

organization. The team designs, develops, and supports enterprise-grade AI applications, including Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI solutions. Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those … success criteria for AI initiatives. Design, develop, and deliver scalable AI solutions, including Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, and intelligent automation capabilities aligned to business objectives. Evaluate technology, model, and platform options, providing recommendations based on business value, cost, risk, strategic ...

features and applications using LLMs, including intelligent document processing, information extraction and automated workflows. Develop retrieval-augmented generation (RAG) solutions that connect LLMs with internal data, documents and other knowledge sources. Build and integrate APIs to connect applications, databases, CRM platforms and third-party … LLMs: Practical experience integrating large language models into applications or developing AI-powered functionality. Retrieval-Augmented Generation (RAG): Experience building or implementing RAG pipelines that enable LLMs to retrieve and use relevant information from documents, databases or other knowledge sources. Application architecture: An understanding ...

enterprise standards. Design enterprise-scale AI architectures covering agent orchestration, large language models (LLMs), retrieval-augmented generation (RAG), knowledge management, integrations, governance, security, and observability. Assess client technology landscapes, data estates, cloud platforms, and security frameworks to establish the foundations required for successful … focused organizations. Technical Knowledge Strong understanding of Large Language Models (LLMs), Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), AI orchestration frameworks, and AI application architectures. Knowledge of cloud platforms including Microsoft Azure, AWS, and Google Cloud. Experience with modern data platforms including Databricks ...

PyTorch FastAPI Knowledge Graphs Kubernetes Docker Infrastructure as Code MLOps Event-Driven Architecture Vector Databases Retrieval-Augmented Generation (RAG) Technology Stack Python SQL FastAPI PyTorch Docker Kubernetes AWS Azure Git CI/CD Knowledge Graphs AI/Large Language Models (LLMs) Amazon Bedrock Azure ...

standards across AI projects. Design and deliver solutions involving generative AI, large language models (LLMs), retrieval-augmented generation (RAG), prompt engineering and agentic AI. Establish robust approaches to model evaluation, monitoring, performance measurement and continuous improvement. Drive high-quality engineering practices, including Python development … machine learning solutions into production. Strong technical leadership and architecture experience across AI engineering and software delivery. Practical knowledge of generative AI, LLMs, RAG, prompt engineering, agentic AI and model evaluation. Strong Python development skills and a sound understanding of software engineering best practice. Experience delivering AI solutions at scale ...

public sector and commercial experience Successful academic background in your specialist discipline Familiarity with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and other patterns used to support Generative AI solutions on platforms such as Amazon Bedrock. Experience developing data-based apps in Streamlit/ ...

cloud technology. You'll take ownership of AI architecture and implementation, designing multi-agent workflows, retrieval-augmented generation (RAG) solutions and AI microservices. Working closely with architects and product teams, you'll turn business requirements into secure, reliable AI applications, with a focus … Python development skills Azure OpenAI and Azure AI Foundry Semantic Kernel and LangGraph Model Context Protocol (MCP) and tool integration Azure AI Search and RAG architecture Multi-agent systems and orchestration workflows Vector databases, embeddings and semantic search Event-driven architectures and REST APIs Docker, Kubernetes and AI microservices MLOps ...

help onboard new team members. Work alongside senior engineers, including colleagues experienced in AI and retrieval-augmented generation (RAG), to build the teams confidence in applying AI to practical problems. Contribute to frontend and backend work according to your experience, developing a broader understanding … problems customers face and how users interact with our products. Explore relevant approaches with senior engineers, drawing on any experience of vector search, embeddings, RAG, fine-tuning, prompt engineering or AI orchestration frameworks such as LangChain. Help evaluate model output quality through structured examples and lightweight evaluation sets. Where relevant ...

Salesforce Einstein or Agentforce. Experience working with in-house or enterprise LLMs, including prompt design, retrieval-augmented generation (RAG) knowledge sources or evaluating AI output quality. Experience with workflow automation tools. Knowledge of the cybersecurity or data security industry. Applicants must be legally authorized ...

Azure AI services. * Build multi-agent systems and AI-powered workflows, integrating with existing applications and data sources. * Apply techniques such as prompt engineering, RAG and agent orchestration to improve AI performance. * Implement AI security, monitoring, testing and governance measures. * Take ownership of solutions throughout the full development lifecycle, from … integration. * Experience with Azure AI services, Azure OpenAI, AI Search or similar technologies. * Understanding of Retrieval-Augmented Generation (RAG), prompt engineering and AI orchestration. * Python experience is desirable but not essential. * Experience working with Public Sector, or other regulated environments would be beneficial. * Must ...

Generative AI technologies. Microsoft Copilot Studio, Power Automate, Azure Logic Apps or Azure Functions. Retrieval-Augmented Generation (RAG) and Azure AI Search. Microsoft 365 or SharePoint integrations. Experience delivering AI solutions within enterprise environments. ...

agent-based patterns, workflow orchestration and enterprise AI integration. Practical experience applying techniques such as retrieval-augmented generation (RAG), knowledge grounding, prompt engineering and human-in-the-loop design patterns. Experience designing secure and controlled AI solutions, including guardrails, responsible AI, explainability and governance ...

machine learning, Generative AI and prompt engineering. Hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and AI evaluation approaches. Strong data analysis, visualisation and statistical modelling skills. Experience managing AI experimentation and model evaluation activities. Understanding of Responsible AI principles ...

Data, AI & Intelligent Systems Expertise: Experience or strong interest in one or more of the following: Generative AI, LLMs, Retrieval Augmented Generation (RAG) and AI applications Agentic AI, AI agents, intelligent assistants and AI-enabled automation Prompt engineering, AI evaluation and Responsible ...

GitHub Actions, Azure DevOps, RBAC and Cost Controls. Software Engineering: Clean Code (SOLID, DRY), DDD, modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens. Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK. ...

experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems Experience designing and scaling low-latency, customer-facing ...

Experience across several of the following areas would be advantageous: * Agentic AI * AI Agents & Autonomous Workflows * Generative AI & LLMs * Retrieval Augmented Generation (RAG) * Multi-Agent Systems * MLOps/LLMOps * LangGraph, LangChain, Semantic Kernel, CrewAI or AutoGen * OpenAI Agents, Microsoft Copilot Studio and MCP * Azure … Agents, Generative AI, LLMs, Machine Learning, Data Science, Platform Engineering, LangGraph, LangChain, Semantic Kernel, CrewAI, OpenAI Agents, Microsoft Copilot Studio, MCP, MLOps, RAG, SaaS, Cambridge. ...

tools (e.g. LangChain, Semantic Kernel, Llama, vector-based search, MCP/Model Context Protocol) into the enterprise architecture. Design and implement RAG (Retrieval-Augmented Generation) architectures, including data ingestion, vector stores, and knowledge layer orchestration. Ensure AI solutions meet security, governance and compliance requirements … building LLM-based applications. Familiarity with Model Context Protocol (MCP) and emerging standards for AI orchestration and context management. Experience designing and implementing RAG architectures in enterprise environments. Background in cloud platforms (e.g. AWS, Azure, GCP) and their AI/ML services. Exposure to knowledge management, knowledge graphs or advanced ...

solutions. You will help clients translate business challenges into scalable AI architectures, leveraging Agentic AI, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and modern cloud technologies. The places that you work from day to day will vary according to your role, your needs … home 100% of the time. Your Role Design and develop enterprise AI solutions, with a particular focus on Agentic AI, Generative AI, and RAG architectures. Work with clients to understand business requirements and translate them into scalable technical solution designs. Build, integrate, and optimize AI applications using Python and leading ...

decisions and mentoring other engineers. Desirable: Python, FastAPI, LangGraph, LangChain or similar AI frameworks. JSON-RPC, SSE, WebSockets and event-driven architectures. Experience with RAG, LLM function calling and context management. An interest in sport and the sports betting industry. Why Consider This Opportunity? This is an opportunity to take ...

Actions, Azure DevOps, RBAC and cost controls. Solid software engineering fundamentals: Clean Code (SOLID, DRY), DDD, modular architecture, TDD and code quality tooling. Desirable: RAG pipelines, MCP, LLM integration (OpenAI, Gemini, Hugging Face models), LangSmith, TruLens, and agentic frameworks such as LangChain, CrewAI, Autogen, OpenAI Agents and Google ADK. … React Developer, Next.js Developer, TypeScript Developer, Azure OpenAI, Vertex AI, LangChain, LangGraph, CrewAI, Autogen, OpenAI Agents SDK, Google ADK, RAG, retrieval augmented generation, MCP, LangSmith, TruLens, prompt engineering, Docker, Kubernetes, AKS, GCP, Azure DevOps, GitHub Actions, PostgreSQL, BigQuery, TDD, DDD. Deerfoot Recruitment Solutions ...

bring a strong STEM/computing background. Knowledge and understanding of UK Defence. Experience in one or more of the following technical disciplines: LLMs, RAG, Agentic AI (e.g. LangGraph). Computer Vision. AI for audio and speech. What we offer We offer a combination of mentoring and internal and external ...

bring a strong STEM/computing background. Knowledge and understanding of UK Defence. Experience in one or more of the following technical disciplines: LLMs, RAG, Agentic AI (e.g. LangGraph). Computer Vision. AI for audio and speech. What we offer We offer a combination of mentoring and internal and external ...

such as Databricks Exposure to evaluating LLM-based applications, including AI-as-a-judge approaches Experience with Generative AI techniques such as retrieval-augmented generation, fine-tuning, or prompt engineering Exposure to distributed data processing frameworks, such as Spark Exposure to fraud detection, anti ...

design and development of AI, Machine Learning, and Generative AI solutions. Drive the adoption of Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and Agentic AI approaches. Define evaluation frameworks, testing strategies, and model performance standards. Act as the technical authority for scientific decisions … What We're Looking For Significant hands-on experience in AI, Machine Learning, and Data Science. Deep expertise with LLMs, Generative AI, Prompt Engineering, RAG, and Agentic Systems. Strong Python programming skills and experience with modern AI frameworks. Excellent understanding of statistics, machine learning methodologies, and model evaluation. Experience delivering ...