1 to 25 of 72 Permanent Retrieval-Augmented Generation Jobs in the UK excluding London

understanding of AI regulations, compliance standards, and security best practices, with a strong focus on Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and secure AI architectures. The ideal candidate will have hands-on experience with LLM security, AI governance frameworks, and regulatory compliance … in a regulated environment, ensuring adherence to AI governance and compliance frameworks. Design and implement Retrieval-Augmented Generation (RAG) architectures to optimize information retrieval for LLMs. Work with Large Language Models (LLMs), fine-tuning, deploying, and integrating them into enterprise systems. Ensure … policies. Essential Skills & Experience AI Development & Deployment: Strong hands-on experience developing and deploying AI/ML models. RAG Expertise: Experience in Retrieval-Augmented Generation and related vector databases (e.g., Pinecone, FAISS, Weaviate). LLMs & NLP: Experience working with LLMs (OpenAI, Anthropic, Hugging Face More ❯

understanding of AI regulations, compliance standards, and security best practices, with a strong focus on Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and secure AI architectures. The ideal candidate will have hands-on experience with LLM security, AI governance frameworks, and regulatory compliance … in a regulated environment, ensuring adherence to AI governance and compliance frameworks. Design and implement Retrieval-Augmented Generation (RAG) architectures to optimize information retrieval for LLMs. Work with Large Language Models (LLMs), fine-tuning, deploying, and integrating them into enterprise systems. Ensure … policies. Essential Skills & Experience AI Development & Deployment: Strong hands-on experience developing and deploying AI/ML models. RAG Expertise: Experience in Retrieval-Augmented Generation and related vector databases (e.g., Pinecone, FAISS, Weaviate). LLMs & NLP: Experience working with LLMs (OpenAI, Anthropic, Hugging Face More ❯

interactions. The role will focus on projects to leverage state-of-the-art generative AI, retrieval-augmented generation (RAG), and reasoning frameworks to build intelligent and context-aware systems. We are seeking talented Machine Learning Engineers with full-stack software development experience to join … relevancy engineering. Conversational AI Development : Design, train, fine-tune, and deploy LLMs with reasoning capabilities. Retrieval-Augmented Generation (RAG): Implement, optimise, and scale RAG pipelines for effective information retrieval from structured and unstructured sources. Model Fine-Tuning & Training : Train domain-specific models … skills & experience: 3-5+ years in machine learning and software development Proficient in Python, PyTorch or TensorFlow or Hugging Face Transformers Experience with RAG, LLM fine-tuning, and expertise in AWS and cloud-native AI deployments. Full-stack experience (React, TypeScript, Node.js) and API development. Familiarity with vector search More ❯

interactions. The role will focus on projects to leverage state-of-the-art generative AI, retrieval-augmented generation (RAG), and reasoning frameworks to build intelligent and context-aware systems. We are seeking talented Machine Learning Engineers with full-stack software development experience to join … relevancy engineering. Conversational AI Development : Design, train, fine-tune, and deploy LLMs with reasoning capabilities. Retrieval-Augmented Generation (RAG): Implement, optimise, and scale RAG pipelines for effective information retrieval from structured and unstructured sources. Model Fine-Tuning & Training : Train domain-specific models … skills & experience: 3-5+ years in machine learning and software development Proficient in Python, PyTorch or TensorFlow or Hugging Face Transformers Experience with RAG, LLM fine-tuning, and expertise in AWS and cloud-native AI deployments. Full-stack experience (React, TypeScript, Node.js) and API development. Familiarity with vector search More ❯

building and optimizing Large Language Model (LLM) inferences and creating robust web services. This includes developing event-driven and request-response systems to run RAG (Retrieval-Augmented Generation) answer generation pipelines, essential for delivering sophisticated AI-driven solutions. Your role will require … an understanding of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code More ❯

natural language processing (NLP) tasks (summarisation, sentiment analysis, keyword extraction, categorisation). Develops and maintains retrieval-augmented generation (RAG) systems, indexing, embedding, and reranking. Builds evaluation frameworks assessing AI output faithfulness, relevance, and truthfulness. Enhances solutions with a focus on efficient compute usage for … with AutoML libraries (e.g., AutoKeras). Solid experience with natural language processing ( NLP ) tasks and retrieval-augmented generation ( RAG ) systems. Expertise in embedding models, indexing techniques, and reranking methods. Familiarity with frameworks and libraries like HuggingFace and LangChain. Deployment: Proficiency with deploying large language … tuning large language models (LLMs). Interest or experience with MCP , A2A , or AutoGen . Keeps up to date with the latest trends in RAG solutions, agentic AI, and generative AI implementations. Behavioural Competencies: Accountability: Takes ownership and responsibility for tasks and outcomes. Proactiveness: Anticipates needs, takes initiative, and seeks More ❯

services You'll connect a variety of APIs (including Claude, OpenAI and others) to enable dynamic conversational agents and intelligent automation. Building Retrieval-Augmented Generation pipelines You'll design smart knowledge retrieval systems using vector databases to enhance the relevance and accuracy … API development and integration , particularly in connecting LLM APIs to external systems. Strong understanding of retrieval-augmented generation (RAG) frameworks and vector databases . Proficiency in Python for developing scalable data and AI solutions, including experience with data processing libraries, API interaction, and structuring … with Claude, AWS Redshift, or graph-based systems like Anzo. So, what's in it for you? The chance to shape the next generation of AI-powered enterprise tools with real business impact. Autonomy to experiment with new technologies and deploy scalable applications in production. Exposure to advanced More ❯

GPT-4, Claude, Gemini, and beyond) Knowledgeable of the latest developments in diffusion models and other generative frameworks for both text and image generation Competent in Generative AI and language models to spearhead innovative initiatives that leverage cutting-edge techniques in NLP and AI Adept at applying advanced … and deployment in production Choose relevant computational tools for study, experiment, or trial research objectives Drive the development of innovative solutions for language generation, text synthesis, and creative content generation using the latest state … of-the-art techniques Develop and implement advanced Generative AI solutions such as intelligent assistants, Retrieval-Augmented Generation (RAG) systems, and other innovative applications Produce clear, concise, well-organized, and error-free computer programs with the appropriate technological stack Present results directly to stakeholders More ❯

for text-heavy datasets. Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-Augmented Generation (RAG). Experience in anomaly detection techniques, algorithms, and applications. Excellent problem-solving, communication (verbal and written), and teamwork skills. Preferred qualifications, capabilities, and skills Experience More ❯

and scaling GenAI models for commercial applications, such as knowledge base creation, recommendation systems, and retrieval-augmented generation (RAG). Key Responsibilities: · Develop and deploy GenAI models tailored for commercial applications. · Implement RAG techniques and other generative AI strategies to enhance business processes. · Ensure More ❯

Technologies : Work with state-of-the-art AI techniques, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), and apply them to real-world business contexts. Cross-Functional Collaboration : Partner with business stakeholders to understand objectives and translate them into actionable machine learning More ❯

for intelligent data discovery, extraction, and decision-making. Oversee the integration of LLMs, knowledge graphs, retrieval-augmented generation (RAG), and reinforcement learning for autonomous task execution. Champion the application of explainable and trustworthy AI principles in all solutions. Hands-on Technical Leadership Serve as … leadership responsibility (people management experience not required). Deep expertise in building intelligent systems with one or more of the following: LLMs, agent frameworks, RAG, knowledge representation, or autonomous data pipelines. Strong programming and software engineering skills (Python preferred; familiarity with cloud-native and MLOps tools). Demonstrated experience in More ❯

Engineer with full-stack development experience to work on cutting-edge projects involving Generative AI , Retrieval-Augmented Generation (RAG) , and multi-agent reasoning frameworks . This is a hands-on, end-to-end engineering role with impact across the full ML lifecycle – from experimentation … to deployment. Conversational AI & Reasoning: Design, fine-tune, and deploy advanced LLMs with agentic capabilities RAG Pipelines: Build and optimise scalable pipelines for structured and unstructured data retrieval LLM Training & Fine-Tuning: Use methods like LoRA, QLoRA, SFT, PEFT, and RLHF Inference & Acceleration: Serve models using vLLM, DeepSpeed … 5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or Hugging Face Proven experience with LLMs, RAG, and deploying cloud-native AI on AWS Strong full-stack skills (React, TypeScript, Node.js) and API development Familiarity with vector databases and multi-agent frameworks Apply More ❯

Engineer with full-stack development experience to work on cutting-edge projects involving Generative AI , Retrieval-Augmented Generation (RAG) , and multi-agent reasoning frameworks . This is a hands-on, end-to-end engineering role with impact across the full ML lifecycle – from experimentation … to deployment. Conversational AI & Reasoning: Design, fine-tune, and deploy advanced LLMs with agentic capabilities RAG Pipelines: Build and optimise scalable pipelines for structured and unstructured data retrieval LLM Training & Fine-Tuning: Use methods like LoRA, QLoRA, SFT, PEFT, and RLHF Inference & Acceleration: Serve models using vLLM, DeepSpeed … 5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or Hugging Face Proven experience with LLMs, RAG, and deploying cloud-native AI on AWS Strong full-stack skills (React, TypeScript, Node.js) and API development Familiarity with vector databases and multi-agent frameworks Apply More ❯

responsible for designing, building, and deploying generative AI solutions across the business. This includes developing Retrieval-Augmented Generation (RAG) pipelines, integrating large language models (LLMs), and deploying services in a secure, scalable cloud environment. You'll work with one of the richest insurance datasets … are robust, compliant, and impactful to our customers and colleagues across the business. Skills and experience we're looking for: Strong experience in GenAI, RAG and Agentic architectures, including popular frameworks like LangChain and LiteLLM. Familiarity with DevOps and CI/CD pipelines, version control (Git), and infrastructure-as-code. More ❯

Hands-on Experience with LLMs : Practical knowledge of working with large language models (LLMs) and retrieval-augmented generation (RAG). Advanced Evaluation Techniques : Expertise in A/B testing, human-in-the-loop evaluation, and GenAI quality metrics, ensuring the quality, relevance, and user More ❯

build and evolve Generative AI (GenAI) proof-of-concepts (POCs) for clients using techniques like Retrieval-Augmented Generation (RAG) and intelligent agents. Support the transition of these POCs into scalable, production-ready solutions. C Contribute to the design and development of full-stack applications More ❯

appropriate trade-o s in design and architecture, particularly when integrating Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) workflows, and other advanced AI technologies. Minimum Qualifications & Experience • 5+ years of experience as a Technical Project Manager or equivalent in managing software and AI … ideally with React and Python stacks, such as Django, FastAPI, or Flask). • Experience delivering AI-driven projects and integrating Large Language Models (LLMs), RAG workflows, or similar technologies (ideally relevant to AVIS or similar products). • End-to-end delivery experience in Agile environments, managing sprints, timelines, and budgets. More ❯

appropriate trade-o s in design and architecture, particularly when integrating Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) workflows, and other advanced AI technologies. Minimum Qualifications & Experience • 5+ years of experience as a Technical Project Manager or equivalent in managing software and AI … ideally with React and Python stacks, such as Django, FastAPI, or Flask). • Experience delivering AI-driven projects and integrating Large Language Models (LLMs), RAG workflows, or similar technologies (ideally relevant to AVIS or similar products). • End-to-end delivery experience in Agile environments, managing sprints, timelines, and budgets. More ❯

build innovative GenAI proof-of-concept (POC) solutions for clients, leveraging cutting-edge technologies like Retrieval-Augmented Generation (RAG) and intelligent agents. Evolve prototype POCs into fully scalable, production-ready solutions that meet client needs. Develop and implement FullStack applications for both GenAI and More ❯

or security frameworks where required (e.g., healthcare, finance, defence). Facilitate integration of LLMs or Retrieval-Augmented Generation (RAG) pipelines, where applicable. Required Experience 2+ years as the primary Technical Project Manager for at least 2 software products shipped to production in the past More ❯

or security frameworks where required (e.g., healthcare, finance, defence). Facilitate integration of LLMs or Retrieval-Augmented Generation (RAG) pipelines, where applicable. Required Experience 2+ years as the primary Technical Project Manager for at least 2 software products shipped to production in the past More ❯

or security frameworks where required (e.g., healthcare, finance, defence). Facilitate integration of LLMs or Retrieval-Augmented Generation (RAG) pipelines, where applicable. Required Experience 2+ years as the primary Technical Project Manager for at least 2 software products shipped to production in the past More ❯

world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to Have: Experience in consulting or client-facing delivery roles Knowledge of cloud platforms More ❯

Prompt-Savvy : Comfortable with prompt engineering, model evaluation, and structured analysis of generative systems. Experimentation First : Experience (or interest) in fine-tuning, instruction tuning, RAG architectures, or guardrail implementation. Collaborative Communicator : Able to bridge the gap between research and product, working across teams to translate ideas into features. Curious & Agile More ❯