1 to 25 of 217 Retrieval-Augmented Generation Jobs in England

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 ❯

and prioritize AI applications that can drive operational efficiency and process improvements. Leverage state-of-the-art GenAI techniques, including Retrieval-Augmented Generation (RAG), AI agents, and other advanced methodologies, to develop robust AI models and solutions. Partner with business leaders and classic business teams to understand their needs and integrate AI solutions seamlessly … a strong focus on practical applications and real-world impact. Demonstrated expertise in GenAI techniques, including but not limited to Retrieval-Augmented Generation (RAG), AI agents, and other advanced AI methodologies. Strong fullstack development experience with TypeScript and React for frontend development coupled with FastAPI/Flask for Python backend services, with additional OfficeJS … API knowledge preferred Extensive knowledge of AI and machine learning ecosystems, including proficiency in modern RAG/Agent frameworks including Langchain/Langgraph, Llamaindex, Pydantic, Vercel AI SDK, and DSPY Strong analytical and problem-solving skills, with the ability to translate complex business requirements into effective AI solutions. Excellent collaboration and communication skills, with the ability to work effectively with 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 ❯

and prioritize AI applications that can drive operational efficiency and process improvements. Leverage state-of-the-art GenAI techniques, including Retrieval-Augmented Generation (RAG), AI agents, and other advanced methodologies, to develop robust AI models and solutions. Partner with business leaders and classic business teams to understand their needs and integrate AI solutions seamlessly … a strong focus on practical applications and real-world impact. Demonstrated expertise in GenAI techniques, including but not limited to Retrieval-Augmented Generation (RAG), AI agents, and other advanced AI methodologies. Strong fullstack development experience with TypeScript and React for frontend development coupled with FastAPI/Flask for Python backend services, with additional OfficeJS … API knowledge preferred Extensive knowledge of AI and machine learning ecosystems, including proficiency in modern RAG/Agent frameworks includingLangchain/Langgraph, Llamaindex, Pydantic, Vercel AI SDK, and DSPY Strong analytical and problem-solving skills, with the ability to translate complex business requirements into effective AI solutions. Excellent collaboration and communication skills, with the ability to work effectively with both 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 ❯

agent planning, tool use integration, multi-agent collaboration). AI Architecture: Deep understanding of AI/ML system architecture patterns, including microservices, event-driven architectures, and patterns specific to RAG (Retrieval-Augmented Generation), Graph RAG, Agentic RAG, and multi-agent systems. Vector Databases & Embeddings: Expertise in working with various embedding models and vector databases 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 ❯

by over 750 civil servants daily. Assist enables government communicators to brainstorm, draft, and review content using Claude (Anthropic) via Amazon Bedrock, enhanced with Retrieval Augmented Generation (RAG), file upload capabilities, and role-specific prompts. This is a unique opportunity to contribute to a business-critical tool with a bold roadmap for FY25 … User Researchers, and Behavioural Scientists to co-design and test product updates. . Contribute to technical decision-making, including Generative AI features such as Retrieval Augmented Generation (RAG), prompt engineering, and application design. . Design and develop new features, including sentiment analysis, data ingestion, and synthetic audience creation, while supporting Agile delivery through sprint More ❯

robust agentic workflows enabling AI agents to interact autonomously with data sources and external APIs using advanced prompt engineering and retrieval-augmented generation (RAG) Fine-tune and optimize pre-trained large language models and multi-modal models for targeted use cases, ensuring high performance and low latency in production. Implement distributed training and scalable 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 ❯

when you meerkat. As Head of Data - Data Science & MLE, you'll lead our advanced analytics and machine learning teams, shaping strategy, driving delivery, and building the next generation of intelligent products. From dynamic pricing to agentic AI and LLMs, this is a pivotal role in bringing our AI strategy to life. This is more than a technical … machine learning and infrastructure-as-code tools (e.g. Terraform, CloudFormation) Exposure to advanced techniques such as large language models (LLMs), retrieval-augmented generation (RAG), and prompt engineering Demonstrated commitment to responsible AI, including experience with model explainability, fairness, or governance frameworks Why Join Us? You'll lead talented teams working on meaningful AI problems 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 ❯

to detail, and a collaborative, growth-focused mindset. Experience working in agile, product-driven engineering teams. Preferred Qualifications: Exposure to Retrieval-Augmented Generation (RAG) pipelines, vector databases (e.g., Pinecone, Weaviate, Milvus), and knowledge bases, with familiarity in integrating them with LLMs. Experience with advanced model monitoring, observability, and governance of LLMs and generative AI 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 ❯

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 ❯

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 ❯

tasks will include: Integrate AI into the SDLC by automating key engineering processesincluding requirements gathering, design, coding, testing, and deploymentusing 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 strategycovering APIs, prompt design, and inference cost management. Enable … 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 ❯

/or large datasets, as well as GenAI. Discover and introduce new technologies to the team, staying up to date with the latest approaches that enable the next generation of Experians products with GenAI and ML. Learn quickly and be able to put new GenAI concepts into practice. Spend 10% of your work time on continuous learning and … learning frameworks and toolkits (e.g., scikit-learn, XGBoost, TensorFlow). Hands-on experience building GenAI solutions using patterns such as Retrieval-Augmented Generation (RAG) or fine-tuning Large Language Models (LLMs). Have experience with cloud computing platforms. Greater familiarity with AWS compared to other cloud computing platforms. Qualifications Have experience in Python Are 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 ❯

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 ❯

experience with cloud platforms (AWS, GCP, Azure) and MLOps workflows. Solid understanding of vector databases (e.g. Pinecone, Weaviate, Milvus) and retrieval-augmented generation (RAG) techniques. Comfort with rapid technical recall for industry benchmarks, model parameters, and framework capabilities. More ❯