126 to 150 of 842 Retrieval-Augmented Generation Jobs in the UK

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

systems in production environments, including performance tuning and cost optimization. Design and build Retrieval-Augmented Generation (RAG) systems using embeddings, vector databases, and semantic search. Build and optimize prompts and interaction strategies for LLMs to achieve desired outcomes in agentic systems. Integrate various tools … multi-agent systems. Familiarity with AI workflow orchestration and agentic frameworks (e.g., LangChain, LangGraph, Crew AI, Haystack, or similar). Practical experience with RAG architectures, embeddings, vector databases, and semantic search. Experience working with Model Context Protocol (MCP) Servers. Experience with RESTful APIs and integrating external services. Solid understanding ...

architectures. Translate business requirements into robust, scalable data solutions. Develop conceptual, logical, and physical data models. Design and implement modern AI-ready architectures, including RAG, vector databases, semantic search, and LLM integrations. Build and optimise data pipelines supporting both batch and real-time processing. Lead data integration, transformation, and migration … modelling experience across enterprise-scale environments. Experience building modern AI-enabled data architectures. Knowledge of Retrieval-Augmented Generation (RAG), vector databases, embeddings, and LLM integrations. Experience with both batch and streaming/real-time data processing. Strong understanding of data governance, quality management, lineage ...

enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns … safe and effective usage within team practices. Working knowledge of LLM application patterns - prompt design, retrieval-augmented generation (RAG), embeddings and vector search, structured output, and tool/function calling. Experience with agentic AI frameworks - multi-agent orchestration, planning and tool use, and integration ...

frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent; Experience with vector databases and retrieval-augmented generation (RAG) patterns; Experience deploying and scaling LLM-powered applications using APIs such as OpenAI or Anthropic, or open-source models; Strong Python skills; Excellent communication skills ...

Lineage, Master Data Management, and enterprise data catalogues. Strong knowledge of Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), LLM integration, Vector Databases, and AI governance frameworks. Significant experience leading technical pre-sales engagements and developing complex solution architectures. Demonstrable experience responding to large ...

learning operations practices Strong working knowledge of large language models (LLMs), including prompting, fine-tuning, retrieval-augmented generation (RAG), and evaluation techniques, and the ability to apply them to real product challenges Experience with agentic AI frameworks and libraries in Python, such ...

learning operations practices Strong working knowledge of large language models (LLMs), including prompting, fine-tuning, retrieval-augmented generation (RAG), and evaluation techniques, and the ability to apply them to real product challenges Experience with agentic AI frameworks and libraries in Python, such ...

learning operations practices Strong working knowledge of large language models (LLMs), including prompting, fine-tuning, retrieval-augmented generation (RAG), and evaluation techniques, and the ability to apply them to real product challenges Experience with agentic AI frameworks and libraries in Python, such ...

cross-functional organizations.Deep knowledge of modern AI technologies including large language models (LLMs), agentic frameworks, retrieval-augmented generation (RAG), vector databases, and automation platforms — with the credibility to evaluate vendor claims and guide architectural decisions.Experience owning AI governance: building acceptable use policies, risk tiering ...

experience of this would be really useful. Building agentic AI solutions, LLM-powered applications and retrieval-augmented generation (RAG) architectures. Experience with Vertex AI Agent Builder, Agentspace, LangGraph or multi-agent frameworks. Knowledge of responsible AI, model governance and risk management practices within regulated ...

world impact. This position sits within a growing AI function and will focus heavily on Retrieval-Augmented Generation (RAG), agentic workflows, evaluation frameworks, and LLM optimisation. Key Responsibilities: Design and develop scalable RAG pipelines and generative AI workflows Build solutions using LangChain, LangGraph … contribute to technical best practices Key Requirements: Strong Python engineering experience Commercial experience building production-grade AI/ML systems Hands-on experience with RAG architectures and LLM workflows Experience with LangChain, LangGraph, and/or Llama Index Understanding of evaluation methodologies for generative AI Experience working within scalable cloud ...

ambiguous environments and owning projects from concept to deployment. Nice to Have Experience with Retrieval-Augmented Generation (RAG). Knowledge of vector databases and semantic search. Experience with Python alongside TypeScript. Familiarity with AI orchestration frameworks such as LangChain, LangGraph, or similar. Experience with … customers. Technologies You'll Work With Generative AI Artificial Intelligence (AI) AWS TypeScript Large Language Models (LLMs) Rapid Prototyping APIs Data Engineering Vector Databases RAG React/Next.js Node.js Git Docker What Success Looks Like Deliver AI solutions that solve real customer problems. Build production-ready applications in weeks ...

business processes.Act as a Salesforce and AI subject matter expert within the Digital Customer Experience (DCX) practice, helping shape our next-generation consulting capabilities and AI delivery methodologies.Design and develop scalable Salesforce solutions using a combination of declarative and programmatic technologies including Apex, Lightning Web Components … Salesforce data.A working understanding of how large language models behave in practice: prompt engineering, retrieval-augmented generation (RAG), grounding, and how to reduce hallucination.Experience testing and evaluating AI features, for example building eval sets, measuring accuracy, and monitoring quality, cost and latency once live.Knowledge ...

business processes. Act as a Salesforce and AI subject matter expert within the Digital Customer Experience (DCX) practice, helping shape our next-generation consulting capabilities and AI delivery methodologies. Design and develop scalable Salesforce solutions using a combination of declarative and programmatic technologies including Apex, Lightning … Salesforce data. • A working understanding of how large language models behave in practice: prompt engineering, retrieval-augmented generation (RAG), grounding, and how to reduce hallucination. • Experience testing and evaluating AI features, for example building eval sets, measuring accuracy, and monitoring quality, cost and latency ...

Build and integrate AI-powered features into web applications and enterprise tools. Build and optimize Retrieval-Augmented Generation (RAG) solutions to power chatbot interactions Work both independently and paired with other team members to ensure efficient delivery of prioritised features. Take part … Experience using modern AI-assisted and agentic development workflows in day-to-day engineering usingAI/ML APIs and SDKs Hands-on experience developing RAG solutions or working with LLMs for chatbots is preferred In-depth understanding of CI/CD and the tools used to implement them, such ...