18 of 18 Retrieval-Augmented Generation Jobs in the East of England

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 ...

within Agile teams and contributing to iterative product delivery Understanding of AI technologies used in legal environments (LLMs, NLP, extraction/classification models, summarisation, RAG pipelines, etc.) Experience working in regulated environments or with legal workflows A product focused and problem-solving mindset with the ability to work independently Ability ...

Strong understanding of automation, workflow optimisation and process re engineering* Experience working within Agile teams* Understanding of AI technologies such as LLMs, NLPs and RAG pipelines* Excellent communication and stakeholder engagement skills* Experience facilitating workshops and discovery sessions What is on Offer * Salary up to £55,000* Hybrid working model ...

Strong understanding of automation, workflow optimisation and process re engineering* Experience working within Agile teams* Understanding of AI technologies such as LLMs, NLPs and RAG pipelines* Excellent communication and stakeholder engagement skills* Experience facilitating workshops and discovery sessions What is on Offer * Salary up to £55,000* Hybrid working model ...

Strong understanding of automation, workflow optimisation and process re engineering* Experience working within Agile teams* Understanding of AI technologies such as LLMs, NLPs and RAG pipelines* Excellent communication and stakeholder engagement skills* Experience facilitating workshops and discovery sessions What is on Offer * Salary up to £55,000* Hybrid working model ...

Business Analyst working within digital, technology, or regulated environments. Strong understanding of AI technologies such as LLMs, NLP, extraction/classification models, or RAG pipelines. Experience improving workflows, automation, or business systems within complex environments. Strong analytical skills with proficiency in process mapping, UML, BPMN or similar. Comfortable facilitating workshops ...

Business Analyst working within digital, technology, or regulated environments. Strong understanding of AI technologies such as LLMs, NLP, extraction/classification models, or RAG pipelines. Experience improving workflows, automation, or business systems within complex environments. Strong analytical skills with proficiency in process mapping, UML, BPMN or similar. Comfortable facilitating workshops ...

architectures, and emerging best practices. What you’ll bring: Expertise in AI and Machine Learning, including agent-based AI, RAG (Retrieval Augmented Generation), multi-agent systems and conversational agents. Strong programming skills in Python, Java or .NET. Experience with GenAI and LLMs (e.g. ChatGPT ...

various AI providers Tool Creation: Developing "Tools" (Function Calling) that allow LLMs to interact with real-world data, enabling features such as consultant lookups (RAG) and clinical system integrations Data Insights: Building pipelines to transcribe and analyse historical call recordings to extract sentiment, summary, and outcome data Prompt Engineering: Refining … understanding of JSON data structures AI/LLM Exposure: Practical experience interacting with LLM APIs (OpenAI, Anthropic, etc.) and understanding concepts like Context Windows, RAG, System Prompts, and Temperature Concurrency: Understanding of asynchronous programming (WebSockets, goroutines) is highly beneficial given the real-time nature of voice data Benefits: 25 Days ...

various AI providers Tool Creation: Developing "Tools" (Function Calling) that allow LLMs to interact with real-world data, enabling features such as consultant lookups (RAG) and clinical system integrations Data Insights: Building pipelines to transcribe and analyse historical call recordings to extract sentiment, summary, and outcome data Prompt Engineering: Refining … understanding of JSON data structures AI/LLM Exposure: Practical experience interacting with LLM APIs (OpenAI, Anthropic, etc.) and understanding concepts like Context Windows, RAG, System Prompts, and Temperature Concurrency: Understanding of asynchronous programming (WebSockets, goroutines) is highly beneficial given the real-time nature of voice data Benefits: 25 Days ...

Product Manager - Hybrid - Cambridge - £55,000 I am working with a highly respected, long-established professional services organisation that is investing in next-generation AI solutions. They are modern, forward-thinking and currently transforming how their teams deliver legal and operational services using automation, LLMs and responsible … Strong understanding of automation, workflow optimisation Experience working in Agile teams (Scrum or Kanban) Knowledge of AI technologies (LLMs, NLP, extraction/classification, summarisation, RAG pipelines, etc.) Experience in regulated environments or legal workflows (advantageous) Strong process-mapping and analytical skills (UML, BPM, modelling tools) Proficiency with tools such ...

growing Business Systems function. With a national presence and a long-established reputation for excellence, the organisation is investing heavily in next-generation technology that enhances service delivery, drives efficiency, and improves client outcomes. The business is known for its collaborative culture, forward-thinking approach, and commitment … Experience working within Agile teams and supporting iterative product delivery Knowledge of AI concepts such as LLMs, NLP, classification/extraction models, summarisation or RAG workflows Ability to simplify complex technical concepts for non-technical audiences Strong stakeholder engagement and workshop-facilitation skills Experience contributing to or leading Agile/ ...