12 of 12 Retrieval-Augmented Generation Jobs in Gloucestershire

ready AI solutions using modern Azure technologies and cloud-native architecture.Integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and Agentic AI capabilities into business applications.Develop responsive frontend applications alongside robust APIs and backend services to create seamless user experiences.Work closely with Product, Business … Services and cloud-native application development.Experience implementing AI solutions including LLM integration, prompt engineering, Retrieval-Augmented Generation (RAG) and vector databases.Experience working with SQL and NoSQL databases, with knowledge of platforms such as SQL Server, Snowflake, OneLake or similar data platforms.Strong understanding of software ...

Azure environment.Define technical standards and best practices for developing advanced Generative AI applications, encompassing complex Retrieval-Augmented Generation (RAG) architectures, prompt and context engineering, and Large Language Model (LLM) integration strategies.Architect innovative Agentic AI systems, establishing frameworks for orchestration, memory management, and robust evaluation.Shape … within Azure environments, with a focus on technical escalation and resolution.Expertise in establishing technical standards and best practices for advanced Generative AI applications, encompassing RAG architectures, prompt engineering, and LLM integration strategies.Experience in architecting and developing Agentic AI systems, including frameworks for orchestration, memory management, and performance evaluation.Advanced knowledge ...

develop, test and deploy LLM and agentic AI solutions Contribute to the development of LLM, Retrieval-Augmented Generation (RAG) and agentic AI solutions, including evaluation, optimisation and monitoring.Implement reliable and scalable AI solutions using established software engineering, MLOps and LLMOps practices.Contribute across … Proven experience engineering technology solutions in complex environments and supporting production operations Applied AI/ML and GenAI experience with knowledge of established patterns (RAG, tool use, guardrails, evaluation, agents) and an ability to evaluate tools and approaches Experience working with conversational AI platforms and customer-facing AI applications. Experience ...

understanding of generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight ...

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 SAP consulting, working with the latest AI agent frameworks, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines to help clients unlock new value, streamline complex processes, and accelerate their digital transformation journeys. This is more than a delivery role. … prioritised, and your career can accelerate quickly. What makes this role different? A specialist innovation focused on SAP consulting, working with AI agents, LLMs, RAG pipelines, and agentic workflows rather than traditional SAP configuration. Exposure to high-profile, complex transformation programmes across multiple industries, delivering cutting-edge technology solutions alongside ...

libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps and production AI practices, including CI/CD, model versioning ...

develop and implement enterprise AI solutions using technologies including Large Language Models, ChatGPT/OpenAI, Microsoft Copilot, Azure AI, Retrieval Augmented Generation (RAG) and UiPath. You'll also develop AI assistants, copilots and automated workflows, integrating AI into systems including ERP, CRM, PLM, SharePoint … have strong technical experience across Python, OpenAI APIs, Prompt Engineering, Azure OpenAI Services, Microsoft Copilot Studio, UiPath, Power Automate, REST APIs and RAG architectures, alongside experience integrating technology into enterprise systems. You'll also be a strong communicator who can translate complex AI concepts for non-technical audiences, work effectively ...

PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation approaches.Experience with MLOps and modern engineering practices, including CI/CD pipelines, model versioning, monitoring and automated ...

Amazon Comprehend, Amazon Transcribe, Amazon Rekognition and related managed AI services.· Generative AI solution design, including foundation model selection, prompt engineering, retrieval-augmented generation, model evaluation, responsible AI controls and enterprise integration patterns.· Data and AI platform architecture on AWS, including data ingestion, governance ...

Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Prompt Engineering: Deep prompt engineering & optimization skills for GenAI.Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI (RAG) for knowledge applications.GenAI ModelOps/MLOps & Governance: GenAI ModelOps/MLOps knowledge … with ethical AI governance focus.Multimodal & Code Generation: Architected GenAI for multimodal (vision, audio, language) & code generation.ER&I GenAI Applications: Applied GenAI to ER&I use cases to create business value.Enterprise Software Integration: Designed GenAI integrations with SaaS/ERP for business process automation.GenAI Impact Reporting: Designed advanced reporting ...