10 of 10 Retrieval-Augmented Generation Jobs in the South West

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 ...

modern vector databases. An understanding of Site Reliability Engineering best practices and Platforms/DevOps best practices. Exposure to AI concepts such as LLMs, RAG, and agent‐based systems (or a strong desire to learn). Experience previously working with central government and an understanding of government ways of working ...

agentic AI architectures, with experience integrating AI securely and at scale Practical experience in enterprise AI governance, prompt engineering, and deployment approaches (including RAG, fine-tuning considerations, and risk mitigation) Experience leveraging AI-assisted development tools (e.g. GitHub Copilot, Claude Code) to materially improve engineering productivity and delivery outcomes ...

delivering solutions at pace. Key Responsibilities Design and build scalable full stack applications Develop and deploy AI-powered solutions including LLM integrations and RAG systems Work closely with stakeholders to translate business needs into technical solutions Lead rapid prototyping and production delivery Contribute to architecture decisions across multiple projects Mentor ...

delivering solutions at pace. Key Responsibilities Design and build scalable full stack applications Develop and deploy AI-powered solutions including LLM integrations and RAG systems Work closely with stakeholders to translate business needs into technical solutions Lead rapid prototyping and production delivery Contribute to architecture decisions across multiple projects Mentor ...

client discovery sessions and pre-sales activities, proposal creation, identifying technology and AI opportunities and defining project scope Proven GenAI and LLM expertise, from RAG and fine-tuning to observability, focused on driving measurable business outcomes Advise on technology and architecture decisions, balancing cost, risk, and performance Advising … client-facing proof of concepts Strong knowledge of cloud platforms (Azure, AWS, GCP) and MLOps best practices Experience with Generative AI and LLMs (e.g., RAG, fine-tuning, prompt engineering) Desirable Degree in Business, Computer Science, Engineering, or related field Personal Attributes Strong analytical and strategic thinking skills Excellent communication skills ...

tactical edge. Own the deployment from infrastructure through to user acceptance. • Build bespoke capability on our platform. Extend our products with customer-specific workflows, RAG pipelines, agentic tooling, data connectors, knowledge graphs and reporting templates. Write production code. Ship it. • Close the loop with product engineering. Feed real operational insight … have seen what breaks between a notebook and a running service, and you know how to fix it • Practical experience with modern AI patterns: RAG, agentic architectures, evaluation, or fine-tuning of LLMs • Fluency with the modern deployment stack: containers, Kubernetes or equivalent, CI/CD, infrastructure-as-code ...