1 to 25 of 213 Retrieval-Augmented Generation Jobs in the UK

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 ❯

classification, object detection, and segmentation production models. Additionally, this role will involve pushing boundaries by building innovative GenAI applications, particularly focusing on API usage and Retrieval Augmented Generation (RAG). You will be joining a team whose mission is to streamline vehicle profiling and transform the online vehicle selling and buying experience for all … of machine learning principles, deep learning techniques and GenAI concepts such as prompt engineering, chain-of-thought reasoning, prompt chaining, Retrieval-Augmented Generation (RAG), custom-built agents. Familiarity with LLM and agentic frameworks like LangChain, PydanticAI, or similar. Proficiency in ML-Ops practices and tools; strong understanding of DevOps and CI/CD. Experience … preferred), GCP, and deploying models in production. Experience developing and shipping GenAI solutions utilising Large Language Models (LLMs), with an emphasis on API usage and Retrieval Augmented Generation (RAG). Proficient in Docker and cloud-based container orchestration services such as AWS Fargate, Google Cloud Run etc. You thrive working on ambiguous problems and More ❯

experts, and UX developers. The role involves: Prototyping AI/NLP tools for policy analysis and consultation feedback processing Building retrieval-augmented generation (RAG) systems to provide policy guidance Preparing datasets and pipelines using structured and unstructured regulatory data Contributing to model evaluation and iteration based on user feedback Developing prototype tools to support … as a short-term contract, whereas a more well-rounded candidate could fit longer-term needs. Desirable Skills Familiarity with retrieval-augmented generation (RAG) architectures Experience with front-end data visualisation Understanding of UAS (drones), aviation, or other regulated industries Involvement in agile software development environments Strong communication skills, particularly the ability to explain 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 ❯

provider (AWS, GCP, Azure) Experience developing AI-driven tools. Familiarity with integrating or building chat and search interfaces, using LLMs for orchestration, vector databases, embedding models, or retrieval-augmented generation (e.g., LangChain, LlamaIndex) Strong product and communication skills. Ability to think strategically beyond tickets, clearly communicate decisions in pull requests, and discuss technical trade … authorization. Comfortable collaborating asynchronously across multiple time zones Contributions to open-source geospatial or AI projects Experience evaluating and improving retrieval-augmented generation (RAG) pipelines (quality assessment, guardrails, and iterative improvement) Familiarity with scientific computing UX (JupyterHub, Binder, etc.) Experience engaging with the broader open-source community through talks, blogs, or forums We collaborate More ❯

tools. You’ll be working on a real-world research platform already in production — now expanding into new territory with retrieval-augmented generation (RAG), vector search, and intelligent automation. In this role, you’ll help reimagine how unstructured and structured data from large-scale surveys and discussions can be turned into clear, actionable insight … using advanced AI. From redesigning RAG stacks to building AI-powered report writers and secure vector stores, you’ll be solving rich, challenging problems at the intersection of NLP, data infrastructure, and human understanding. Whether you’ve shipped AI features before or have strong personal research and projects, this is a chance to shape products used by real researchers and … real human thoughts, opinions, and behaviours — at scale. 🧠 LLM Research Meets Real Deployment : Prototype and productionise advanced AI features like conversational survey assistants, automated Q&A, and thematic summarisation. 📦 RAG, Vector Search & Pipelines : Redesign and optimise RAG pipelines, create secure vector-based knowledge repositories, and build survey data transformation services. 🔧 MLOps & Evaluation : Own testing, evaluation harnesses, prompt management, and observability More ❯

foundation into our cloud-native SaaS platform. This role is ideal for innovative developers eager to design, implement and integrate into Lucanet ecosystem scalable AI solutions, focusing on APIs, RAG architectures, and agentic frameworks. It's an exciting opportunity to shape the future of our platform, to work in an agile environment, with the latest technologies including AI based coding … assistants and bring your ideas to life. What you'll do Design and implement scalable AI/ML solutions, focusing on APIs, RAG architectures, and agentic frameworks Work closely with cross-functional teams, product managers to understand business requirements and translate them into technical specifications Test and deploy software solutions that meet business needs Participate in code reviews to ensure … Protocol (MCP) and how to build AI agents that can leverage MCP servers (would be a great plus) Knowledge of Retrieval-Augmented Generation (RAG) techniques to enhance model responses by integrating external knowledge bases during inference (would be a great plus) Perks at work LucaFlex - We acknowledge that every individual has different working styles More ❯

Job Description What will you be doing? This role presents an opportunity to engage deeply with MLOps, vector databases, and Retrieval-Augmented Generation (RAG) pipelines - skills that are in incredibly high demand. If you are passionate about shaping the future of AI and thrive on complex, high-impact challenges, we encourage you to apply. … data solutions, ensuring efficiency, scalability, and cost-effectiveness. Power Generative AI: Develop and manage specialized data flows for generative AI applications, including integrating with vector databases and constructing sophisticated RAG pipelines. Champion Data Governance & Ethical AI: Implement best practices for data quality, lineage, privacy, and security, ensuring our AI systems are developed and used responsibly and ethically. Tooling the Future … dataset versioning. Vector Database Experience: Practical experience working with vector databases (e.g., Pinecone, Milvus, Chroma) for embedding storage and retrieval. Generative AI Familiarity: Understanding of data paradigms for LLMs, RAG architectures, and how data pipelines support fine-tuning or pre-training. MLOps Principles: Familiarity with MLOps best practices for deploying and managing ML models in production. Data Governance & Ethics: Experience More ❯

transformation, summarization, and retrieval-based tasks. • Develop prompt-driven automation systems for workflows including metadata extraction, tagging, reporting, and anomaly detection. • Design and deploy RAG (Retrieval-Augmented Generation) and embedding-based search solutions integrated with enterprise knowledge bases. Agent Orchestration & Autonomy • Build intelligent agents using CrewAI, LangChain or similar frameworks to support … use cases like automated report generation, root cause analysis, and interactive user agents. • Implement feedback and memory mechanisms to support context-aware, evolving agents. AI-Native API & Platform Integrations • Develop, manage, and scale API integrations that connect AI workflows with data warehouses , business tools , and external data sources . • Create intelligent endpoints for model inference, decision logging, and … knowledge for structured data operations and AI-data interplay. Nice to Have • Google Cloud certifications in Data or Machine Learning. • Experience with vector databases , embedding generation , and RAG infrastructure. • Exposure to autonomous agent memory systems , reward tuning, or action planning loops. • Familiarity with Data Engineering process and tools. More ❯

large-scale web crawls to internal datasets - and connect them to cutting-edge AI models, including fine-tuned LLMs and retrieval-augmented generation (RAG) pipelines. Our solutions enable smarter property decisions, faster operations, and better customer outcomes for both the financial services and property sectors. Key Responsibilities Data Acquisition & Integration Design, implement, and operate … pipelines ingesting and normalising data from APIs, databases, web crawlers, and file imports. Architect secure, scalable web crawling and data ingestion systems suitable for regulated environments. AI Development & RAG Implementation Prepare, clean, and structure datasets for fine-tuning LLMs and retrieval-based workflows. Design, implement, and optimise RAG pipelines using vector databases, embeddings, and semantic search to connect … complex data pipelines from multiple sources. Strong expertise in large-scale web crawling & scraping . Proficiency in Python and one or more of: Node.js, Go, Java. Deep experience in RAG - from embeddings and vector database design to semantic search optimisation and retrieval integration with LLMs. Experience with LLM fine-tuning and evaluation. Hands-on experience with GPU cloud More ❯

large-scale web crawls to internal datasets - and connect them to cutting-edge AI models, including fine-tuned LLMs and retrieval-augmented generation (RAG) pipelines. Our solutions enable smarter property decisions, faster operations, and better customer outcomes for both the financial services and property sectors. Key Responsibilities Data Acquisition & Integration Design, implement, and operate … pipelines ingesting and normalising data from APIs, databases, web crawlers, and file imports. Architect secure, scalable web crawling and data ingestion systems suitable for regulated environments. AI Development & RAG Implementation Prepare, clean, and structure datasets for fine-tuning LLMs and retrieval-based workflows. Design, implement, and optimise RAG pipelines using vector databases, embeddings, and semantic search to connect … complex data pipelines from multiple sources. Strong expertise in large-scale web crawling & scraping . Proficiency in Python and one or more of: Node.js, Go, Java. Deep experience in RAG - from embeddings and vector database design to semantic search optimisation and retrieval integration with LLMs. Experience with LLM fine-tuning and evaluation. Hands-on experience with GPU cloud 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 ❯

data augmentation, transfer learning, and hyperparameter tuning to optimise model performance on complex datasets Expertise in implementing hybrid search and retrieval-augmented generation (RAG) techniques Solid understanding of Large Language Models, including how to apply multi-modal models and when to apply prompt engineering and fine-tuning. Deployment and Cloud-based 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 ❯

rapid iteration, prompt engineering, and practical application. You'll fine-tune and optimize foundation models, craft sophisticated multi-agent systems, and invent novel solutions to power the next generation of voice intelligence. What You'll Do Integrate AI solutions into existing products and workflows Collaborate with cross-functional teams to understand business requirements and translate them into technical … AWS, Google Cloud, or Azure Knowledge of Kubernetes and containerization technologies Experience with data science and ML engineering Familiarity with retrieval-augmented generation (RAG) The requirements listed in the job descriptions are guidelines. You don't have to satisfy every requirement or meet every qualification listed. If your skills are transferable we would still More ❯

Certain Advantage are recruiting on behalf of our Trading client for an AI Data Scientist who can bring a strong understanding in modern NLP, LLMs, transformer architectures, prompt-engineering, RAG, agentic architectures and evaluation methodologies.They require candidates to offer strong knowledge of Python programming for developing and debugging AI models and would expect suitable candidates to be educated to an … within the GenAI/NLP team. This role will focus on the application and development of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and domain-specific GenAI solutions to support key internal use cases and products. Responsibilities In this role you will: Design, implement and maintain scalable NLP and GenAI pipelines (including … to date with state-of-the-art research in the space of LLMs/NLP, proposing new ideas and methodologies that unlock business value. Contribute to the development of RAG systems and retrieval pipelines, including chunking, embedding, re-ranking, and evaluation. Participate in experiments, including designing experimental details, writing reusable code, running evaluations, and organising results. Collaborate with More ❯

in production. Expertise in data augmentation , transfer learning , and hyperparameter tuning for complex datasets. Strong understanding of hybrid search and retrieval-augmented generation (RAG) techniques. Solid experience with Large Language Models (LLMs) , including multi-modal models and applying prompt engineering and fine-tuning . Experience deploying models via cloud platforms (AWS, GCP) and using More ❯

in AI Solution Architecture, including LLM/SLM (Large Language Models/Small Language Models) deployment, fine-tuning, inference optimization, retrieval-augmented generation (RAG), API-based AI deployment and model orchestration. Strong knowledge of Cloud AI & Hyperscalers, including AWS Bedrock, OpenAI, Google Vertex AI, Azure, hybrid and multimodal AI applications. Proficiency in Cloud Security More ❯

and model serving on platforms like AWS, Azure, or GCP. Experience with Large Language Models (LLMs), model fine-tuning, and Retrieval-Augmented Generation (RAG) pipelines. Experience in developing enterprise-grade applications that leverage data-driven decision-making. Responsibilities Develop, maintain, and optimize backend services and APIs using Python, ensuring high performance and scalability. Design More ❯

support our AI & data science solutions. This includes the application of Generative AI technologies, such as large language models (LLMs), Retrieval-Augmented Generation (RAG) pipelines, and prompt engineering-to build intelligent tools and enhance knowledge-based workflows. This is a fantastic opportunity for someone with foundational analytical expertise, eager to learn and grow in … client projects. You will be involved in: Applying data science best practices and standards across projects. Assisting in the design and implementation of Generative AI applications, including LLM workflows, RAG architectures, and prompt engineering. Collaborating with stakeholders to identify opportunities where GenAI can streamline tasks, automate insights, or improve decision-making. Gathering, processing, and managing data from disparate sources, ensuring … including ETL pipelines. Skills in data analysis, visualization, and storytelling with data. Analytical problem-solving and critical thinking abilities. Awareness of Generative AI techniques, including LLMs, prompt engineering, and RAG approaches. Experience with tools/frameworks for building Generative AI applications (e.g., agentic AI, orchestration frameworks, embedding models, vector databases). Understanding of machine learning and predictive modelling. Proficiency in More ❯

include: Integrate AI into the SDLC by automating key engineering processes—including requirements gathering, design, coding, testing, and deployment—using tools like OpenAI Codex, ChatGPT Enterprise, Claude, OpenRouter, and RAG-based systems. Streamline Dev Workflows by embedding LLMs and RAG pipelines into daily development operations for smarter, faster delivery. Drive DevOps Automation by partnering with DevOps and SaaS leadership to … Matters by collaborating with Internal Audit to track AI performance gains and quantify automation ROI. Build AI-First Internal Tools by developing intelligent tools like prompt libraries, test generators, RAG-powered knowledge bots, and automated documentation writers. Lead on AI Integration by providing hands-on technical leadership in AI/LLM strategy—covering APIs, prompt design, and inference cost management. … LLM agents and tools into real-world engineering or product organizations Deep expertise with modern AI ecosystems, including: LangChain OpenRouter Retrieval-Augmented Generation (RAG) pipelines OpenWebUI and other dev-facing AI interfaces Background in or strong familiarity with AI-native companies Hands-on ability to own strategy and execution: from vision to POCs to More ❯

include: Integrate AI into the SDLC by automating key engineering processes—including requirements gathering, design, coding, testing, and deployment—using tools like OpenAI Codex, ChatGPT Enterprise, Claude, OpenRouter, and RAG-based systems. Streamline Dev Workflows by embedding LLMs and RAG pipelines into daily development operations for smarter, faster delivery. Drive DevOps Automation by partnering with DevOps and SaaS leadership to … Matters by collaborating with Internal Audit to track AI performance gains and quantify automation ROI. Build AI-First Internal Tools by developing intelligent tools like prompt libraries, test generators, RAG-powered knowledge bots, and automated documentation writers. Lead on AI Integration by providing hands-on technical leadership in AI/LLM strategy—covering APIs, prompt design, and inference cost management. … LLM agents and tools into real-world engineering or product organizations Deep expertise with modern AI ecosystems, including: LangChain OpenRouter Retrieval-Augmented Generation (RAG) pipelines OpenWebUI and other dev-facing AI interfaces Background in or strong familiarity with AI-native companies Hands-on ability to own strategy and execution: from vision to POCs to More ❯

automate complex legal workflows and enhance user experiences. Advanced Technology Integration: Collaborate on projects that leverage emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs - to enhance our core product and explore new use cases. Cross-Functional Collaboration: Work closely with cross-functional teams to integrate advanced ML models and NLP solutions More ❯