151 to 175 of 963 Retrieval-Augmented Generation Jobs in 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 ...

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 ...

across the organisation. Build AI assistants, copilots, intelligent automation tools and knowledge management solutions. Develop Retrieval-Augmented Generation (RAG) solutions using internal business data. Create scalable AI architectures and support the ongoing management of AI platforms and infrastructure. Integrate AI solutions with business-critical … experience building and deploying AI or Machine Learning solutions. Strong Python development skills. Experience working with REST APIs and systems integration. Knowledge of LLMs, RAG architectures, vector databases and modern AI frameworks. Experience with AWS cloud services and infrastructure. Familiarity with Docker and Kubernetes. Experience integrating AI solutions with Microsoft ...

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

build analytical tools, AI-assisted insight products, and intelligent automation — including prompt engineering and retrieval-augmented generation (RAG). Validate all AI and model outputs for accuracy, bias, and reliability before they reach stakeholders.Translate reporting and analytical findings into clear, business-ready insight … data analysis, modelling, and scripting.Machine learning — knowledge in building and applying supervised and unsupervised models to real business problems.Generative AI and LLMs — prompt engineering, RAG, and applied use of LLM tooling in an analytical context.Automation tooling — experience with platforms such as Power Platform, Power Automate, or equivalent.Communication, business requirements ...

build analytical tools, AI-assisted insight products, and intelligent automation — including prompt engineering and retrieval-augmented generation (RAG). Validate all AI and model outputs for accuracy, bias, and reliability before they reach stakeholders.Translate reporting and analytical findings into clear, business-ready insight … data analysis, modelling, and scripting.Machine learning — knowledge in building and applying supervised and unsupervised models to real business problems.Generative AI and LLMs — prompt engineering, RAG, and applied use of LLM tooling in an analytical context.Automation tooling — experience with platforms such as Power Platform, Power Automate, or equivalent.Communication, business requirements ...

ClinicalKey AI, PharmaPendium, and next-generation life sciences platforms. These products leverage retrieval-augmented generation (RAG), semantic search, and generative AI to make knowledge more discoverable, connected, and actionable across disciplines.The Search & AI Evaluation team sits within the Platform Data Science organization … indexing, ranking, query understanding)Exposure to clickstream data, user behavior analytics, and event tracking systemsExperience supporting evaluation of ML-based ranking or retrieval systemsFamiliarity with RAG systems or GenAI applicationsWhy join us Join our team and contribute to a culture of innovation, collaboration, and excellence. ...

ClinicalKey AI, PharmaPendium, and next-generation life sciences platforms. These products leverage retrieval-augmented generation (RAG), semantic search, and generative AI to make knowledge more discoverable, connected, and actionable across disciplines. The Search & AI Evaluation team sits within the Platform Data Science … clickstream data, user behavior analytics, and event tracking systems Experience supporting evaluation of ML-based ranking or retrieval systems Familiarity with RAG systems or GenAI applications Why join us? Join our team and contribute to a culture of innovation, collaboration, and excellence. If you are ready to advance ...

opportunity As a Contact Centre & CX Architect within Deloitte's Engineering practice, you will play a key role in designing and delivering next-generation customer engagement solutions for some of the world's leading organisations. Working across complex transformation programmes, you will help clients modernise customer operations through … centre implementations.Experience with AI-powered customer engagement solutions, including Conversational AI, Generative AI, virtual assistants, Retrieval-Augmented Generation (RAG), knowledge management, and intelligent automation.Connect to your business - Technology and TransformationDistinctive thinking, deep expertise, innovation and collaborative working. That’s what connects us. That ...

Company DescriptionAt IFS, we're building the next generation of AI-native enterprise software, transforming how some of the world's largest organisations manage assets, operations and critical services. This is an opportunity to work at the forefront of modern AI engineering, building intelligent products that combine Large … with Large Language Models (LLMs) within enterprise applications.Understanding of modern AI application patterns such as Retrieval-Augmented Generation (RAG), tool calling, prompt engineering and agentic workflows where appropriate.Experience evaluating AI-enabled features for quality, reliability, performance, security and operational readiness.Experience using AI-assisted engineering ...

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 ...

systems, including role definition, tool integration, planning, memory, and workflow orchestration using modern agent frameworks.Implement Retrieval-Augmented Generation (RAG) pipelines and semantic search with vector databases, including indexing, retrieval policies, and evaluation.Build and integrate agent tools and APIs to connect agents with ...

similar customer‐facing role. Experience building AI applications using modern LLM, agentic AI and retrieval-augmented generation (RAG) frameworks. Bachelor's degree or equivalent commercial experience. Cloud platform certifications (Azure, AWS or Google Cloud). Architecture certifications such as TOGAF or equivalent. Experience working ...

including role definition, tool integration, planning, memory, and workflow orchestration using modern agent frameworks. Implement Retrieval-Augmented Generation (RAG) pipelines and semantic search with vector databases, including indexing, retrieval policies, and evaluation. Build and integrate agent tools and APIs to connect agents ...

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 ...

machine learning operations practicesStrong 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 challengesExperience with agentic AI frameworks and libraries in Python, such as AWS Bedrock ...

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 ...

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 ...

tooling — such as LangGraph, LangChain, LlamaIndex, or CrewAI — and how they are appliedExperience with retrieval-augmented generation (RAG) architectures, vector databases, and LLM-powered applications as part of a commerce or customer technology programmeFamiliarity with CI/CD pipelines, containerisation, and cloud-native deployment ...

Learning: Expertise in time-series forecasting, clustering, and correlation algorithms.Generative AI: Experience with LLM prompting, Retrieval-Augmented Generation (RAG), and LangChain.Cloud Infrastructure: Deep understanding of AWS, Azure, or GCP infrastructure componentsAdditional Preferred Qualifications:Experience with enterprise observability and AIOps platforms such as ServiceNow ITOM ...

Expertise in time-series forecasting, clustering, and correlation algorithms. Generative AI: Experience with LLM prompting, Retrieval-Augmented Generation (RAG), and LangChain. Cloud Infrastructure: Deep understanding of AWS, Azure, or GCP infrastructure componentsAdditional Preferred Qualifications: Experience with enterprise observability and AIOps platforms such as ServiceNow ...

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 ...