20 of 20 Retrieval-Augmented Generation Jobs in the 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 ...

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 ...

unlock value Building solutions using Large Language Models (LLMs), Agentic/autonomous AI workflows, Retrieval-Augmented Generation (RAG), Modern AI tooling (e.g. LangChain, vector databases, APIs) Rapidly prototyping and iterating on solutions within fast-paced timelines Translating complex technical concepts into practical, commercial outcomes … Looking For Strong software engineering fundamentals (Python, APIs, version control, testing) Experience working with modern AI technologies, such as LLMs/Generative AI, RAG pipelines, Agent-based architectures Ability to work in fast-paced, ambiguous environments and deliver tangible outcomes quickly Strong communication skills and comfort working in client-facing ...

journey The key things they are looking for are: Strong Python skills A good general understanding of LLMs Some exposure to GenAI, chatbots, NLP, RAG, prompt engineering or similar An interest in AI guardrails and responsible use of AI Good software engineering principles Awareness of security in modern development ...

/LLM systems to production. Strong Python + software engineering fundamentals (testing, code quality, CI/CD). Experience with modern LLM patterns (RAG, tool use/agents, fine-tuning or prompt systems) and robust evaluation. Practical experience operating production systems on-prem or in a private cloud (Linux, containers ...

EventBridge, SQS, Step Functions Databases: DynamoDB, PostgreSQL, Aurora, MongoDB Frontend: React, TypeScript, MUI DevOps: AWS CDK, Terraform, Docker, GitLab CI, CodePipeline AI: Amazon Bedrock, RAG, LLM integrations Skills Required Commercial software engineering experience Strong AWS cloud/serverless experience Strong backend development skills in TypeScript, Python, or Go CI/ ...

agent-style or multi-step AI workflows Using LLMs (Azure OpenAI/OpenAI) in real applications Implementing prompt engineering in production environments Working with RAG, embeddings, or vector-based search Designing systems with human-in-the-loop controls and governance Understanding of AI reliability, evaluation, and auditability This ...

software engineering best practices. Support end-to-end MLOps processes including deployment, monitoring and model validation. Explore and implement generative AI capabilities including LLMs, RAG pipelines, and intelligent workflow automation. Key Skills: Commercial experience in Machine Learning Engineering, Applied AI, or related software engineering roles. Strong programming skills in Python … pipelines, and scalable deployment practices. Understanding of MLOps concepts including experiment tracking, model monitoring, and reproducibility. Exposure to Generative AI technologies including LLMs, RAG, or prompt engineering is a plus. Strong communication skills and ability to work effectively within cross-functional agile teams. ...

Postgres and Snowflake, plus caching layers like Redis Designing SQL-based data models and working with distributed data workflows Integrating LLM-driven capabilities (e.g. RAG/CAG architectures) into production grade systems. If big systems, AI initiatives and modern tech get you fired up, this could be your next move. ...

hands-on software engineering background with experience writing production code Proven experience managing and growing engineering teams Strong understanding of AI concepts including LLMs, RAG, and AI-enabled architectures Genuine interest in AI technologies and modern software development practices Experience delivering high-quality SaaS or digital products in agile environments ...

leading and developing engineering teams, including growing high-performing teams and improving delivery effectiveness. Strong understanding of modern AI concepts and architectures, including LLMs, RAG, and fine-tuning, with the ability to assess AI-driven technical proposals independently. Genuine interest in AI and emerging technologies, with hands-on experimentation using ...

operational software — turning fragmented operational data into structured, trusted intelligence. We're focused on difficult, practical problems: Text-to-SQL against real enterprise schemas RAG over messy operational data Screen recorded workflow mapping Workflow and knowledge tooling that operational teams will actually adopt The platform is being developed alongside … t. Tech you'll touch Laravel · Livewire · Alpine · Tailwind · Python · SQL Server (T-SQL) · PostgreSQL · Power BI/DAX · Docker · GitHub · LLM integrations · RAG · embeddings · Claude Code & Cursor daily Logistics Location: Fully remote, UK Hours: Full-time Type: Contract-to-perm. Outside IR35. Salary: £70,000–£80,000 on conversion ...