1 to 25 of 61 Permanent Retrieval-Augmented Generation Jobs in the UK excluding London

AI expert ready to take your skills to the next level? Do words like Azure OpenAI, Cognitive Services, prompt engineering, Retrieval-Augmented Generation (RAG) architectures, vector stores, and API integrations make you light up inside? If so, we want to hear from you! At 1st Central , we're on an exciting journey with AI … develop AI and Generative AI solutions using services like Azure OpenAI and Azure Cognitive Services Implement prompt engineering techniques and Retrieval-Augmented Generation (RAG) architectures. Ensure scalability, security, auditability, and efficiency of AI solutions through detailed system design and development practices. Deploy and manage AI solutions via CI/CD pipelines in Azure DevOps … deploying, and managing production-grade AI and Generative AI systems. Extensive experience with Cloud-based AI and Cognitive Services, and Retrieval-Augmented Generation (RAG) architectures. Deep expertise in API integration, preferably within the Azure ecosystem. Experience with Infrastructure as Code (IaC) across development, testing, and production environments. Solid understanding of Azure networking principles, security More ❯

AI expert ready to take your skills to the next level? Do words like Azure OpenAI, Cognitive Services, prompt engineering, Retrieval-Augmented Generation (RAG) architectures, vector stores, and API integrations make you light up inside? If so, we want to hear from you! At 1st Central , we're on an exciting journey with AI … develop AI and Generative AI solutions using services like Azure OpenAI and Azure Cognitive Services Implement prompt engineering techniques and Retrieval-Augmented Generation (RAG) architectures. Ensure scalability, security, auditability, and efficiency of AI solutions through detailed system design and development practices. Deploy and manage AI solutions via CI/CD pipelines in Azure DevOps … deploying, and managing production-grade AI and Generative AI systems. Extensive experience with Cloud-based AI and Cognitive Services, and Retrieval-Augmented Generation (RAG) architectures. Deep expertise in API integration, preferably within the Azure ecosystem. Experience with Infrastructure as Code (IaC) across development, testing, and production environments. Solid understanding of Azure networking principles, security More ❯

for a Data Scientist with strong NLP and Python skills, and hands-on experience with large language models (LLMs) and Retrieval-Augmented Generation (RAG). You'll be comfortable developing production-ready AI tools and collaborating across engineering, IT, and business functions. About the role: We're hiring a Data Scientist specialising in NLP … internal users across diverse teams - from design and manufacturing to systems engineering - developing tools powered by large language models (LLMs), Retrieval-Augmented Generation (RAG), and modern NLP techniques. From data preparation to algorithm design and deployment, you'll own the full data science lifecycle and help shape the future of AI capability across the … formed GenAI team, with plenty of opportunity to influence tooling, architecture, and strategy. Key Responsibilities: Design and deliver NLP and LLM-based algorithms tailored to internal user needs Apply RAG methods to provide accurate, context-rich AI responses using internal data Work with stakeholders across engineering, manufacturing, and systems teams to translate needs into AI solutions Clean, process, and manage More ❯

manage contract execution, search and retrieval, royalty calculations, and insight generation - increasingly supported by AI and retrieval-augmented generation (RAG) capabilities. We are looking for an Assistant Product Owner to support the evolution and delivery of this ecosystem, working alongside a lead Product Manager and cross-functional teams across Sales … Have Skills and Experience Exposure to internal business systems such as CRM, contract lifecycle management, or licensing platforms Understanding of AI-powered tools and document search (e.g. retrieval-augmented generation) Familiarity with Agile product delivery and tools such as Jira, Confluence, or Azure DevOps Basic knowledge of cloud services (AWS, Azure, GCP) Agile or More ❯

using python and SQL The ability to build AI-driven solutions using large language models (LLMs), and techniques such as retrieval-augmented generation (RAG) and agent-based approaches, supported by frameworks like LangChain and CrewAI Skills in leveraging AI model APIs (e.g. OpenAI, Anthropic) and rapid prototyping tools such as Streamlit, along with AI More ❯

Conduct research on the latest AI advancements and implement innovative solutions. Assist in fine-tuning large language models (LLMs) and retrieval-augmented generation (RAG) systems. Optimize model performance and work on deployment strategies using cloud-based AI solutions. Support MLOps best practices to streamline AI development workflows. Stay updated with the latest advancements in … in AI/ML development. Generative AI experience with Hugging Face, fine-tuning open-source LLMs like Mistral/Llama/Gemma/Phi/Qwen, vLLM, Text Generation Inference, unsloth, LoRA, adapters, DPO, ORPO, hugging face inference endpoints, LlamaIndex Experience with embeddings, vector databases, and deep learning models. Hands-on experience with cloud AI services (AWS, GCP More ❯

and services so they can create brilliant technology solutions for UK businesses. We're seeking a Senior Software developer, to work predominantly on the adoption of AI & code generation tooling across a wide range ofproducts. This role is a hybrid role with the expectation of minimum 1-2 days per week, working from our Hessle office (nr Hull … Doing Analyse business requirements and translate them into intelligent, scalable solutions using C# and .NET. Design and implement AI-powered developer tools and services, including prompt-based code generation, smart documentation, and internal copilots. Own the end-to-end integration of LLMs and AI APIs (e.g., OpenAI, Azure OpenAI), including prompt design, evaluation, and optimization-without relying on … environment. Nice to Have: Experience with LangChain, Semantic Kernel , or similar orchestration frameworks. Familiarity with embedding models , vector stores, or retrieval-augmented generation (RAG). Contributions to open-source AI/dev tools or participation in AI hackathons. What's in it for you? Remote/Hybrid working The chance to work in a More ❯

and Experience : Exposure to hardware design or verification processes (e.g., RTL, formal verification, simulation workflows). Familiarity with vector search, retrieval-augmented generation (RAG), or multi-agent orchestration. In Return: At Arm, you'll work on AI challenges with practical impact across a global organization. You'll join a collaborative team that values deep … technical insight, clean engineering and creative problem-solving. Your contributions will influence how thousands of engineers at Arm design and verify the next generation of computing platforms-smarter, faster, and at scale. Accommodations at Arm At Arm, we want to build extraordinary teams. If you need an adjustment or an accommodation during the recruitment process, please email . More ❯

with enterprise partners. No two weeks will look the same. Fine-tune and privately deploy LLMs - with a focus on Retrieval-Augmented Generation (RAG) pipelines Build and scale computer vision systems - from object detection to image segmentation Apply NLP to real-world business problems - summarisation, entity recognition, information extraction, and more Train and deploy More ❯

and love building innovative solutions from scratch, this could be the perfect role for you. What you'll be doing Building and refining LLM-based agents, including retrieval-augmented generation and data retrieval systems. Designing AI-powered system architecture using Python, Java, and SQL/NoSQL databases. Fine-tuning models (LLMs & SLMs … Essential: Strong experience with Gen AI, NLP, and machine learning. Proven ability to create, train, and fine-tune LLMs/SLMs. Skills in prompt engineering and RAG (retrieval-augmented generation). Solid background in Python, Java, and database technologies (SQL/NoSQL). Experience in crawling/web scraping and API development. Experience with More ❯

Expertise Experience working with Large Language Models (LLMs) and understanding of trade-offs between performance, cost, and capability. Understanding of Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, and tool calling. Familiarity with AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A). Strong knowledge or experience in working with various ML More ❯

Expertise Experience working with Large Language Models (LLMs) and understanding of trade-offs between performance, cost, and capability. Understanding of Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, and tool calling. Familiarity with AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A). Strong knowledge or experience in working with various ML More ❯

Data Factory, Azure Synapse, and Azure Functions. Implementing modern retrieval techniques such as vector search, semantic search and Retrieval-Augmented Generation (RAG) using tools like Azure Cognitive Search, FAISS, Pinecone, or Weaviate. Familiarity with data governance, privacy, and ethical AI principles. Experience with DevOps tools and practices, including CI/CD pipelines More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of More ❯

Strong understanding of AI technologies, including machine learning, natural language processing, or computer vision; or mathematical optimization. Experience with LLMs and Generative AI techniques such as fine tuning, pruning, RAG systems, transfer learning etc. Excellent command of Python, Docker and Git. Experience with GitHub/Gitlab workflows and functionalities. Solid understanding of agile development methodologies and best practices. Excellent leadership More ❯

Experience with distributed computing for large-scale ML workloads (Spark). Experience with pricing models or pricing-related projects is strongly preferred. Additional Experience in GenAI projects implementation (multiple RAG patterns, prompt management, agentic workflows) is preferred. You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business More ❯

machine learning, data science or a related STEM field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business solutions. More ❯

machine learning, data science or a related STEM field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business solutions. More ❯

machine learning, data science or a related STEM field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business solutions. More ❯

machine learning, data science or a related STEM field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business solutions. More ❯