101 to 125 of 279 Retrieval-Augmented Generation Jobs in the UK

AI Engineers x 2 + fully remote contract + initially 6 months + £500 to £530 per day - Inside IR35 Key Skills: + Design of Gen AI Models + RAG + AI/ML Pipelines The Role: + Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for enterprise use … cases. + Build and fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). + Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. + Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or … . Ensure compliance with AI ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape AI use cases. Contribute to More ❯

on experience deploying ML models in production environments. Excellent programming skills in Python and familiarity with ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex). Experience working with LLM APIs (e.g. Hugging Face, OpenAI). Exposure to conversational AI platforms (Dialogflow, Lex, Rasa, etc.). Ability to work More ❯

on experience deploying ML models in production environments. Excellent programming skills in Python and familiarity with ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex). Experience working with LLM APIs (e.g. Hugging Face, OpenAI). Exposure to conversational AI platforms (Dialogflow, Lex, Rasa, etc.). Ability to work More ❯

stakeholders Empower teams to scale AI across the organisation Maintain technology RADAR and manage AI governance and risk Required Skills & Experience Production experience with Generative AI, LLMs, NLP, and RAG systems Strong knowledge of Knowledge Graphs and semantic technologies Proficient in Python, SQL, PyTorch/TensorFlow Experience with DevOps, CI/CD, DevSecOps and secure ML pipelines. Proven experience in More ❯

stakeholders Empower teams to scale AI across the organisation Maintain technology RADAR and manage AI governance and risk Required Skills & Experience Production experience with Generative AI, LLMs, NLP, and RAG systems Strong knowledge of Knowledge Graphs and semantic technologies Proficient in Python, SQL, PyTorch/TensorFlow Experience with DevOps, CI/CD, DevSecOps and secure ML pipelines. Proven experience in More ❯

Bachelor’s or Master’s degree in a STEM field (Computer Science, Data Science, Engineering, Mathematics, etc.). Strong proficiency in Python Hands-on experience with LLMs , prompt design , RAG architectures , or fine-tuning foundation models . Understanding of MLOps practices (e.g., Docker, FastAPI, MLflow, cloud-based model deployment). Strong grasp of NLP techniques and evaluation methods for generative More ❯

enterprise use cases. Build and fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js … . Ensure compliance with AI ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape AI use cases. Contribute to More ❯

leading a small, high-performing team. What You’ll Do Build and maintain data pipelines and cloud infrastructure (AWS/GCP). Develop AI-driven applications including LLM tools, RAG pipelines, and automation solutions. Lead on client communication , project delivery, and stakeholder alignment. Collaborate with Data Science and Analytics teams to improve data access, automation, and governance. Drive innovation through More ❯

Solid understanding of REST APIs, cloud platforms (Azure/AWS/GCP), and agile delivery A passion for clean code, scalability, and technical excellence Nice to Have Experience with RAG systems, multi-agent AI, or Langfuse/LiteLLM Python proficiency for AI/ML integration Familiarity with MLOps and cost optimisation for AI systems Background in B2B SaaS or financial More ❯

and TypeScript, Familiarity with Agentic Frameworks (e.g. LangChain, LangGraph) Proven experience building full stack applications using Git, SQL databases and modern deployment practices Understanding of LLMs, embedding models and RAG systems Solid software engineering fundamentals and secure coding practices Strong problem-solving, communication and teamwork skills At least 3 years hands-on engineering experience in project delivery environments Attention to More ❯

principles and software testing practices. Experience delivering customer-facing products and supporting the full development lifecycle. Excellent communication, stakeholder engagement, and advisory skills. Desirable Experience with Generative AI, LLMs, RAG, LangChain, or Semantic Kernel. Familiarity with Microsoft Power Platform. Front-end experience with React, Angular, Vue.js, Flutter, or Progressive Web Apps. Exposure to edge computing, VR/AR, or robotics. More ❯

principles and software testing practices. Experience delivering customer-facing products and supporting the full development lifecycle. Excellent communication, stakeholder engagement, and advisory skills. Desirable Experience with Generative AI, LLMs, RAG, LangChain, or Semantic Kernel. Familiarity with Microsoft Power Platform. Front-end experience with React, Angular, Vue.js, Flutter, or Progressive Web Apps. Exposure to edge computing, VR/AR, or robotics. More ❯

and Generative AI R&D. Strong understanding of machine learning, data modelling , and natural language processing (NLP) techniques. Experience with fine-tuning , prompt orchestration , and retrieval methods (RAG, knowledge graphs). Familiarity with frameworks such as LangGraph , Azure AI Foundry Agents , and Semantic Kernel Agents . Good understanding of software engineering best practices , including version control, testing, and More ❯

and defining success metrics. Contribute reusable components and frameworks for faster deployments. Qualifications 3+ years building production-grade AI/data solutions. Hands-on GenAI experience (LLMs, prompt engineering, RAG, vector databases, agentic frameworks like LangChain, LlamaIndex, DSPy). Strong Python proficiency with a GitHub portfolio showcasing MLE or GenAI projects. Expertise in Machine Learning Engineering (model development, deployment, monitoring More ❯

and defining success metrics. Contribute reusable components and frameworks for faster deployments. Qualifications 3+ years building production-grade AI/data solutions. Hands-on GenAI experience (LLMs, prompt engineering, RAG, vector databases, agentic frameworks like LangChain, LlamaIndex, DSPy). Strong Python proficiency with a GitHub portfolio showcasing MLE or GenAI projects. Expertise in Machine Learning Engineering (model development, deployment, monitoring More ❯

with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). More ❯

with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). More ❯

links to your GitHub or StackOverflow to showcase your projects and personal passion for AI and Software Engineering. Keywords/Tech Focus: Python, Node.JS, GenAI, LLM, Agentic AI, MLOps, RAG, LangChain, LlamaIndex, AWS, TypeScript, Docker, Terraform, SaaS, London More ❯

platforms (Azure, AWS, or GCP) Agile mindset with focus on testing, observability, and secure delivery Excellent communication and cross-functional collaboration skills Nice to have Experience with vector databases , RAG systems , or multi-agent AI Python skills for AI/ML development Familiarity with MLOps , Langfuse , or LiteLLM Background in fintech , SaaS , or payments software Join a forward-thinking fintech More ❯

Architect multi-step agent workflows using: Semantic Kernel SDK (C# or Python) Azure OpenAI (GPT-4, function calling, chat completion) Planner and Kernel Memory APIs for reasoning and memory RAG pipelines grounded in enterprise data via Azure AI Search Enterprise Data & AI Services Integration: Azure AI Search (vector indexing, hybrid search) Azure Form Recognizer for document understanding Azure Language Services More ❯

the Senior AI Engineer Design, build and deploy AI/ML systems that drive measurable business impact. Apply advanced AI techniques - deep learning, GNNs, object detection, sensor fusion, embeddings, RAG and generative AI - to create adaptive, self-learning solutions. Provide guidance on AI architecture and scalable deployment for autonomous, high-performance systems. Collaborate with cross-functional teams to deliver AI More ❯

Must-Haves: Technical Chops 5+ years software engineering in production environments Strong in Node.js/TypeScript and Python Experience building microservices architectures Hands-on AI/ML integration (LLMs, RAG, agent frameworks) Cloud infrastructure expertise (GCP/AWS/Azure) Real-time systems and async processing experience Leadership 2+ years leading engineering teams (3-10 people) Proven track record hiring More ❯

Must-Haves: Technical Chops 5+ years software engineering in production environments Strong in Node.js/TypeScript and Python Experience building microservices architectures Hands-on AI/ML integration (LLMs, RAG, agent frameworks) Cloud infrastructure expertise (GCP/AWS/Azure) Real-time systems and async processing experience Leadership 2+ years leading engineering teams (3-10 people) Proven track record hiring More ❯

experience building and deploying machine learning models in a production environment. Strong programming skills and deep expertise in Python. Hands-on experience building with agentic or RAG (Retrieval-Augmented Generation) frameworks like LangChain or LlamaIndex. Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers More ❯

experience building and deploying machine learning models in a production environment. Strong programming skills and deep expertise in Python. Hands-on experience building with agentic or RAG (Retrieval-Augmented Generation) frameworks like LangChain or LlamaIndex. Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers More ❯