23 of 23 Permanent Retrieval-Augmented Generation Jobs in the East Midlands

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 ...

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 ...

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 ...

most cutting-edge defence and aerospace projects in the UK? If the prospect of developing software for projects such as a sixth-generation stealth fighter jet or a revolutionary Laser Directed Energy product excites you, then Leonardo would like to hear from you. Leonardo is seeking to recruit … fine-tuning large language models (LLMs). Experience building scalable pipelines, including APIs, vector databases, retrieval-augmented generation (RAG), and orchestration frameworks. Experience curating datasets, managing embeddings, and ensuring security, privacy, and responsible AI practices. Experience in prompt engineering, with the ability to design ...

data pipelines and platform components Experience of coaching and mentoring data engineers to achieve successful outcomes Familiarity with AI-focused data engineering, including RAG systems, vector databases, embedding pipelines, and semantic indexing A proven record of collaboration with colleagues and stakeholders Process mapping and supporting documentation production Test plan formulation ...

integrating Generative AI/LLM functionality directly into software products Working with technologies such as OpenAI, Azure OpenAI, Claude, Gemini or local models Exploring RAG, AI agents, Semantic Kernel, MCP, vector search and intelligent workflows Engineering around the realities of production AI: accuracy, security, validation, guardrails, latency and cost Working ...

multi-cloud or hybrid environmentsExposure to Infrastructure as Code (e.g., Terraform, CloudFormation)Experience in large-scale, complex, or regulated environmentsKnowledge of vector databases and RAG architectures for building internal SRE knowledge assistants.Knowledge of Generative AI and LLM platforms (e.g., Claude, Amazon Bedrock)Person SpecificationStrong technical authority with the ability ...

multi-cloud or hybrid environmentsExposure to Infrastructure as Code (e.g., Terraform, CloudFormation)Experience in large-scale, complex, or regulated environmentsKnowledge of vector databases and RAG architectures for building internal SRE knowledge assistants. Knowledge of Generative AI and LLM platforms (e.g., Claude, Amazon Bedrock)Person SpecificationStrong technical authority with the ability ...

multi-cloud or hybrid environmentsExposure to Infrastructure as Code (e.g., Terraform, CloudFormation)Experience in large-scale, complex, or regulated environmentsKnowledge of vector databases and RAG architectures for building internal SRE knowledge assistants.Knowledge of Generative AI and LLM platforms (e.g., Claude, Amazon Bedrock)Person SpecificationStrong technical authority with the ability ...

multi-cloud or hybrid environmentsExposure to Infrastructure as Code (e.g., Terraform, CloudFormation)Experience in large-scale, complex, or regulated environmentsKnowledge of vector databases and RAG architectures for building internal SRE knowledge assistants. Knowledge of Generative AI and LLM platforms (e.g., Claude, Amazon Bedrock)Person SpecificationStrong technical authority with the ability ...

equivalentsPrompt engineering, context design and agentic workflow frameworksEvaluation harnesses, evaluation datasets and automated test suites for AI outputsRetrieval-augmented generation (RAG), vector search, embeddings and retrieval pipelines (desirable)LLM orchestration frameworks (LangChain, Semantic Kernel or equivalents – desirable)Technical and Professional ExpertiseStrong software engineering background … GitHub Copilot, Cursor or equivalents, with a practical view of where they help and where they mislead.Preferred Qualifications and ExperienceRetrieval-augmented generation, agentic workflows, tool use or fine-tuning in production settings.Experience with LLM APIs, orchestration frameworks, vector search, embeddings, retrieval pipelines, evaluation datasets ...

equivalentsPrompt engineering, context design and agentic workflow frameworksEvaluation harnesses, evaluation datasets and automated test suites for AI outputsRetrieval-augmented generation (RAG), vector search, embeddings and retrieval pipelines (desirable)LLM orchestration frameworks (LangChain, Semantic Kernel or equivalents – desirable)Technical and Professional ExpertiseStrong software engineering background … Copilot, Cursor or equivalents, with a practical view of where they help and where they mislead. Preferred Qualifications and ExperienceRetrieval-augmented generation, agentic workflows, tool use or fine-tuning in production settings. Experience with LLM APIs, orchestration frameworks, vector search, embeddings, retrieval pipelines, evaluation ...

language model APIs across multiple providersAI coding tools: GitHub Copilot, Cursor or equivalentsPrompt engineering and context design patternsRetrieval-augmented generation (RAG), vector search, embeddings (desirable)Evaluation frameworks and automated quality pipelines for AI outputsTechnical and Professional ExpertiseSolid production experience with C# .NET, including working in established … results to improve quality.Daily fluency with AI coding tools such as GitHub Copilot, Cursor or equivalents.Preferred Qualifications and ExperienceRetrieval-augmented generation, agentic workflows, tool use, vector search or embeddings in production settings.Experience with LLM APIs across more than one provider, with a feel for their trade ...

language model APIs across multiple providersAI coding tools: GitHub Copilot, Cursor or equivalentsPrompt engineering and context design patternsRetrieval-augmented generation (RAG), vector search, embeddings (desirable)Evaluation frameworks and automated quality pipelines for AI outputsTechnical and Professional ExpertiseSolid production experience with C# .NET, including working in established … improve quality. Daily fluency with AI coding tools such as GitHub Copilot, Cursor or equivalents. Preferred Qualifications and ExperienceRetrieval-augmented generation, agentic workflows, tool use, vector search or embeddings in production settings. Experience with LLM APIs across more than one provider, with a feel for their ...

experience across some or all of the following: Generative AI, Large Language Models (LLMs), AI assistants and AI agents. Retrieval Augmented Generation (RAG), enterprise search and knowledge management solutions. Solution, platform or enterprise architecture. Data architecture, integration, APIs and governance. Security, compliance, risk management ...

language model APIs across multiple providersAI coding tools: GitHub Copilot, Cursor or equivalentsPrompt engineering and context design patternsRetrieval-augmented generation (RAG), vector search, embeddings (desirable)Evaluation frameworks and automated quality pipelines for AI outputsTechnical and Professional ExpertiseSolid production experience with C# .NET, including working in established … improve quality. Daily fluency with AI coding tools such as GitHub Copilot, Cursor or equivalents. Preferred Qualifications and ExperienceRetrieval-augmented generation, agentic workflows, tool use, vector search or embeddings in production settings. Experience with LLM APIs across more than one provider, with a feel for their ...

powered features within a modern C#/.NET application stack. Integrate Large Language Models (LLMs) and Generative AI into customer-facing products. Build RAG pipelines using vector databases and semantic search. Develop APIs and backend services that support AI functionality at scale. Work closely with Product, Engineering and Data teams … looking for Strong commercial experience developing backend applications in C# and .NET. Experience integrating AI or LLM technologies into production software. Understanding of RAG, embeddings, prompt engineering and vector search. Experience building scalable cloud-based applications using Azure. A genuine interest in Applied AI and solving real-world product problems. ...

develop AI-powered features within a modern C#/.NET application stack.Integrate Large Language Models (LLMs) and Generative AI into customer-facing products.Build RAG pipelines using vector databases and semantic search.Develop APIs and backend services that support AI functionality at scale.Work closely with Product, Engineering and Data teams to deliver … ServerREST APIsMicroservicesDockerWhat we're looking forStrong commercial experience developing backend applications in C# and .NET.Experience integrating AI or LLM technologies into production software.Understanding of RAG, embeddings, prompt engineering and vector search.Experience building scalable cloud-based applications using Azure.A genuine interest in Applied AI and solving real-world product problems.What ...