19 of 19 Permanent Retrieval-Augmented Generation Jobs in the West Midlands

call for an AI agent that orchestrates data sources and tools; another may require a Retrieval-Augmented Generation (RAG) system over internal knowledge; another may be an AI layer embedded into an existing business process or platform. What stays consistent across … apply will be required for this role.Key responsibilities:Design and build the appropriate AI solution for each initiative, whether that is an agent, a RAG pipeline, a document processing system, or something elseIntegrate foundation models (via API) into business applications and workflowsDevelop MCP (Model Context Protocol) servers and tool integrations ...

field. Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection). Strong Python skills with a grounding in software engineering best practices ...

field. Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection). Strong Python skills with a grounding in software engineering best practices ...

principles and engineering excellence. Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG), agentic AI, model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection). Strong Python skills with a grounding in software engineering ...

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 ...

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 … 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 ...

reinforcement learning and LLMs. Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG) and agentic AI. Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc). Expertise in data ...

reinforcement learning and LLMs. Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG), and agentic AI. Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc). Expertise in data ...

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 ...

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 ...

LLMs and agentic AI. Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG) and orchestration of agentic AI systems. Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data, and integrating non-traditional data sources. ...

Azure, including SaaS and PaaS offerings. Hands-on experience building and deploying with modern AI, including large language models and agentic AI (prompt engineering, RAG, tool and function calling, orchestration), on the Microsoft AI stack such as Azure OpenAI, Azure AI Foundry and Azure AI services. Proven experience of technical ...

agentic AI systems for enterprise clients, in partnership with leading frontier-model providers. We already support clients from different verticals to have agentic and RAG systems live in production across healthcare, financial services, retail and global logistics. As a Forward Deployed AI Engineer you work embedded in the client … least one of: Anthropic Agent SDK, LangGraph, LlamaIndex, or an equivalent orchestration framework, plus the judgement to know when to use none of them. RAG and retrieval: Chunking strategy, embeddings, hybrid and semantic search, re‐ranking, citation and provenance, natural‐language‐to‐query translation. Data platforms: NoSQL databases ...

Language Models (LLMs), AI-assisted development tools, and modern AI frameworks. Has understanding of AI system architecture, prompt engineering, vector databases, RAG (Retrieval-Augmented Generation), and AI service integration and has experience evaluating Has knowledge of database systems and excellent problem-solving skills ...

with Azure OpenAI, Azure AI Document Intelligence or comparable cloud-based AI and document-processing services. Experience designing solutions involving generative AI, retrieval-augmented generation or AI agents. Knowledge of secure prompt design, model governance, data privacy and responsible AI controls. Experience with ...

Star" for tech people involved in the implementation of AI related solutions.Provide technical oversight and architecture reviews for AI related projects.Monitor emerging AI patterns (RAG, Fine-tuning, Multi-agent systems).Collaborate with the AI & Data Transformation Lead to support Value Streams and Support Functions on advisory support for AI uses … business requirements with engineering execution. Experience with enterprise-scale systems, security standards, and AI governance is critical.Skills:Expertise in AI design patterns (such as RAG, Fine-tuning, and Agentic workflows) and model evaluation frameworks. Strong technical leadership and mentorship abilities, exceptional stakeholder management across cross-functional teams (Security, Data, Infrastructure ...

tech people involved in the implementation of AI related solutions. Provide technical oversight and architecture reviews for AI related projects. Monitor emerging AI patterns (RAG, Fine-tuning, Multi-agent systems).Collaborate with the AI & Data Transformation Lead to support Value Streams and Support Functions on advisory support for AI uses … business requirements with engineering execution. Experience with enterprise-scale systems, security standards, and AI governance is critical.Skills:Expertise in AI design patterns (such as RAG, Fine-tuning, and Agentic workflows) and model evaluation frameworks. Strong technical leadership and mentorship abilities, exceptional stakeholder management across cross-functional teams (Security, Data, Infrastructure ...