18 of 18 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 ...

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 ...

implementing AI agents, automation workflows and AI-powered business solutions. Strong understanding of prompt engineering, Retrieval-Augmented Generation (RAG), tool/function calling and LLM integrations. Excellent business analysis, stakeholder management and workshop facilitation skills. Ability to translate complex business requirements into practical, scalable ...

core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, Deep Learning, etc. ...

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 ...

real-world systems. What you'll work on: Integrating AI components (including LLMs) into production applications and workflows Designing and implementing RAG (Retrieval-Augmented Generation) systems Evaluating LLM behavior, identifying failure modes, and implementing mitigation strategies Testing and debugging non-deterministic AI systems …/CD, IaC, testing, containers) Practical experience with AI systems, including LLM behavior and architectures Evaluation techniques and failure mode analysis Experience with RAG and applied AI system design Strong understanding of AI limitations and appropriate use cases Excellent communication and stakeholder engagement skills Eligibility for UK SC-level security ...

experience with Docker, Linux/Unix CLI, Git, and testing Understanding of modern AI approaches, including: Agentic AI systems RAG (Retrieval Augmented Generation) Graph-based approaches Computer vision, audio, or multimodal models Knowledge of data governance and security best practices Strong communication and problem … solutions in secure environments High-performance computing and cloud-native AI architectures End-to-end MLOps lifecycle and model management Advanced AI techniques including RAG, agentic systems, and multimodal models Secure, high-assurance data environments Modern DevOps, CI/CD, and engineering practices Why Join? Work at the forefront ...

zones, networking, security, governance) Design scalable cloud, data, and AI solutions Deliver modern data platforms (Fabric, Databricks, data lakes) Shape AI solutions (Azure OpenAI, RAG, copilots) Run client workshops and act as technical lead on engagements Support pre-sales, bids, and solution design What Were Looking For 610+ years Azure ...

consulting, a delivery role at a SaaS/AI company, or a technical role you've moved out of. Experience with LLM-based products, RAG, or agentic systems. PMP, PRINCE2, Agile/Scrum certifications. How You Work You're comfortable with ambiguity and bring structure to it. You ask good ...

will be involved across the full lifecycle of GenAI productsfrom proof of concept through to scalable production deployment and monitoring. Working with modern LLMs, RAG architectures and agentic frameworks , youll collaborate with data engineers, solution architects and business stakeholders to deliver secure, cost-effective AI solutions on AWS. Key Responsibilities … Design and implement production GenAI applications using LLMs (e.g. Anthropic, AWS Bedrock models) Build and deploy RAG systems using vector databases and semantic search Develop agentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI or similar Create effective prompt engineering strategies with appropriate guardrails for production systems Implement monitoring ...

delivering innovative machine learning solutions: Building and deploying LLMs and ML models (cloud or HPC) Leading technical delivery across projects Driving adoption of GenAI, RAG, and agent-based systems Acting as the SME for ML engineering and deployment Tech Focus Python, Docker, Linux, Git AWS or Azure CI/… MLOps pipelines Exposure to RAG, computer vision, or multimodal AI Why Apply? Work on next-generation AI use cases Strong focus on innovation and career progression Opportunity to lead and shape technical direction Security clearance eligibility required. ...

reusable agent components and playbooks Proactively surface new automation opportunities across the business Key Skills Python & LLM agent frameworks (LangChain, CrewAI, LlamaIndex) Prompt engineering & RAG pipelines Business analysis & stakeholder management Process mapping & workshop facilitation Microsoft 365 & Microsoft Copilot No-code/low-code tooling (Zapier, Make) Desirable Skills Experience … etc. Strong enough technically to assess feasibility and scope what is buildable; commercially sharp enough to prioritise what is worth building. Familiarity with LLMs, RAG pipelines, tool/function calling, and integrating AI into real business workflows. Proven ability to lead discovery workshops and translate complex business problems into clear ...