8 of 8 Permanent Retrieval-Augmented Generation Jobs in Bedfordshire

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 ...

Requirements 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 ...

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 ...

Proven experience as an AI or Machine Learning Engineer with end-to-end model ownership Strong expertise in NLP and LLMs (transformers, fine-tuning, RAG, agents) Experience translating research and experimentation into production systems Solid understanding of MLOps, including CI/CD, monitoring and model lifecycle management Hands-on experience ...

shape how GenAI and ML are used across the platform. Tech stack: Python PyTorch or TensorFlow scikit-learn Spark Kafka Databricks LangChain and RAG-based GenAI systems Cloud-native Azure environment Important Details: Fully remote across the UK Up to £80,000 - £100,000 (DOE) 2-3 stage interview process ...

Requirements: · 6–10+ years software engineering experience · 2–4+ years building AI/LLM systems in production · Experience building agentic workflows (tool calling, orchestration, RAG) · Strong backend engineering (Strong in Python essential) · API integrations with enterprise systems · Experience with vector databases and structured retrieval · Cloud deployment (AWS/ ...

Summary About: Kalisa is a GenAI platform turning knowledge and expertise into secure AI solutions, in minutes. Core skills required: Python, Flask, LangChain, RAG, Generative AI product development, LLMs, Guard railing, anti-hallucination techniques and GenAI evaluation techniques. Other skills considered: Tailwind CSS, HTMX, AWS or Azure or GCP Please … JavaScript overhead and improving the overall user experience. No prior HTMX experience is required. GenAI Integration: Work with LangChain to implement prompt engineering techniques, RAG pipelines, and intelligent agent capabilities. RAG & Vector Databases: Implement and optimise RAG strategies, semantic search capabilities, and embeddings-based retrieval; integrate and manage ...

systems across internal tooling, developer workflows, and customer-facing products. You'll own the end-to-end build of production AI systems, from RAG pipelines and multi-agent architectures to LLM integration, fine-tuning, and workflow automation. Core Skills: Python/TypeScript/JavaScript LangChain RAG at scale LLM fine ...