1 to 25 of 226 Retrieval-Augmented Generation Jobs in London

looking for a highly skilled Lead AI Solutions Engineer to design, build, and optimize a Retrieval-Augmented Generation (RAG) system that underpins our self-serve analytics data applications. In this pivotal position, you will develop a scalable RAG platform, integrate multiple data sources, and … create intuitive data interactions to empower teams across the organization. As part of our Group's RAG Initiative, you will collaborate with a cross-functional team to implement self-service AI-driven solutions - ranging from NLP Data Analysis and Data Discovery to other analytics assistants we will be deploying to … s about reshaping our operational DNA to drive innovation, efficiency, and exceptional customer experiences in the new era of analytics and automation. Key Responsibilities: RAG System Development Enhance, build new assistants and maintain existing scalable and modular RAG architectures for data retrieval and generation. Develop APIs and microservices More ❯

faster, smarter decisions through contextual, AI-powered insights. Squirro's Enterprise GenAI Platform combines Search, Retrieval-Augmented Generation (RAG), and LLM-based components to surface actionable insights from unstructured data. Designed to integrate seamlessly with existing systems and workflows, the platform supports key use … Senior AI Engineer to design and develop the Generative AI capabilities within our Insight Engine. You'll work at the intersection of LLMs, Search, RAG, and NLP, creating production-ready systems that solve real business problems. You will be in the driver's seat in shaping the future of Squirro … to augment decision-making across use cases like, search, summarization, recommendations, and Q&A. Design Retrieval-Augmented Generation (RAG) pipelines to ground LLMs with customer-specific context and data. Develop & educate prompt strategies and support the design of abstractions for prompt reuse and testing. More ❯

Develop prototypes and experimental models to explore novel AI-driven legal solutions. Design and implement retrieval-augmented generation (RAG) pipelines , leveraging embeddings, vector databases, and structured retrieval techniques. Optimise LLM inference and fine-tuning using techniques such as LoRA, PEFT, prompt engineering … Python, Pydantic, FastAPI, and working with LLM APIs (OpenAI, Anthropic, Mistral, etc.) . Understanding of retrieval-augmented generation (RAG), vector databases, embeddings, and structured AI retrieval . Hands-on experience with LLM-based planning, reasoning, and autonomous task execution . Familiarity with More ❯

Develop prototypes and experimental models to explore novel AI-driven legal solutions. Design and implement retrieval-augmented generation (RAG) pipelines , leveraging embeddings, vector databases, and structured retrieval techniques. Optimise LLM inference and fine-tuning using techniques such as LoRA, PEFT, prompt engineering … Python, Pydantic, FastAPI, and working with LLM APIs (OpenAI, Anthropic, Mistral, etc.) . Understanding of retrieval-augmented generation (RAG), vector databases, embeddings, and structured AI retrieval . Hands-on experience with LLM-based planning, reasoning, and autonomous task execution . Familiarity with More ❯

Develop prototypes and experimental models to explore novel AI-driven legal solutions. Design and implement retrieval-augmented generation (RAG) pipelines , leveraging embeddings, vector databases, and structured retrieval techniques. Optimise LLM inference and fine-tuning using techniques such as LoRA, PEFT, prompt engineering … Python, Pydantic, FastAPI, and working with LLM APIs (OpenAI, Anthropic, Mistral, etc.) . Understanding of retrieval-augmented generation (RAG), vector databases, embeddings, and structured AI retrieval . Hands-on experience with LLM-based planning, reasoning, and autonomous task execution . Familiarity with More ❯

Develop prototypes and experimental models to explore novel AI-driven legal solutions. Design and implement retrieval-augmented generation (RAG) pipelines , leveraging embeddings, vector databases, and structured retrieval techniques. Optimise LLM inference and fine-tuning using techniques such as LoRA, PEFT, prompt engineering … Python, Pydantic, FastAPI, and working with LLM APIs (OpenAI, Anthropic, Mistral, etc.) . Understanding of retrieval-augmented generation (RAG), vector databases, embeddings, and structured AI retrieval . Hands-on experience with LLM-based planning, reasoning, and autonomous task execution . Familiarity with More ❯

to redefine primary care while helping people live happier, healthier, and longer. Education Masters Degree About the Role You will design, build, and optimize RAG pipelines that combine large language models (LLMs) with domain-specific retrieval systems, enabling natural language understanding and reasoning over patient data, clinical guidelines … work will directly impact how patients and clinicians interact with our platform, enabling safe, accurate, and context-aware content surfacing. Responsibilities Design and implement RAG architectures using open-source and potentially proprietary LLMs (e.g., LLaMA, Mistral, OpenAI, Anthropic). Build and maintain retrieval pipelines over structured and unstructured … notes, device logs, clinical documentation). Develop indexing strategies using vector databases (e.g., FAISS, Weaviate, Pinecone) and embedding models (e.g., BioBERT, ClinicalBERT). Integrate RAG outputs into user-facing applications, ensuring responses are grounded, reliable, and privacy-compliant. Work closely with product, clinical, and data science teams to fine-tune More ❯

to redefine primary care while helping people live happier, healthier, and longer. Education Masters Degree About the Role You will design, build, and optimize RAG pipelines that combine large language models (LLMs) with domain-specific retrieval systems, enabling natural language understanding and reasoning over patient data, clinical guidelines … work will directly impact how patients and clinicians interact with our platform, enabling safe, accurate, and context-aware content surfacing. Responsibilities Design and implement RAG architectures using open-source and potentially proprietary LLMs (e.g., LLaMA, Mistral, OpenAI, Anthropic). Build and maintain retrieval pipelines over structured and unstructured … notes, device logs, clinical documentation). Develop indexing strategies using vector databases (e.g., FAISS, Weaviate, Pinecone) and embedding models (e.g., BioBERT, ClinicalBERT). Integrate RAG outputs into user-facing applications, ensuring responses are grounded, reliable, and privacy-compliant. Work closely with product, clinical, and data science teams to fine-tune More ❯

to redefine primary care while helping people live happier, healthier, and longer. Education Masters Degree About the Role You will design, build, and optimize RAG pipelines that combine large language models (LLMs) with domain-specific retrieval systems, enabling natural language understanding and reasoning over patient data, clinical guidelines … work will directly impact how patients and clinicians interact with our platform, enabling safe, accurate, and context-aware content surfacing. Responsibilities Design and implement RAG architectures using open-source and potentially proprietary LLMs (e.g., LLaMA, Mistral, OpenAI, Anthropic). Build and maintain retrieval pipelines over structured and unstructured … notes, device logs, clinical documentation). Develop indexing strategies using vector databases (e.g., FAISS, Weaviate, Pinecone) and embedding models (e.g., BioBERT, ClinicalBERT). Integrate RAG outputs into user-facing applications, ensuring responses are grounded, reliable, and privacy-compliant. Work closely with product, clinical, and data science teams to fine-tune More ❯

to redefine primary care while helping people live happier, healthier, and longer. Education Masters Degree About the Role You will design, build, and optimize RAG pipelines that combine large language models (LLMs) with domain-specific retrieval systems, enabling natural language understanding and reasoning over patient data, clinical guidelines … work will directly impact how patients and clinicians interact with our platform, enabling safe, accurate, and context-aware content surfacing. Responsibilities Design and implement RAG architectures using open-source and potentially proprietary LLMs (e.g., LLaMA, Mistral, OpenAI, Anthropic). Build and maintain retrieval pipelines over structured and unstructured … notes, device logs, clinical documentation). Develop indexing strategies using vector databases (e.g., FAISS, Weaviate, Pinecone) and embedding models (e.g., BioBERT, ClinicalBERT). Integrate RAG outputs into user-facing applications, ensuring responses are grounded, reliable, and privacy-compliant. Work closely with product, clinical, and data science teams to fine-tune More ❯

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. More ❯

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. 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 ❯

exciting point in our journey, leveraging Generative AI (GenAI) , Large Language Models (LLMs) , and advanced Retrieval-Augmented Generation (RAG) techniques to build intelligent, data-driven systems that deliver powerful PR insights. You'll also work on developing agentic workflows that autonomously orchestrate tasks, enabling More ❯

exciting point in our journey, leveraging Generative AI (GenAI) , Large Language Models (LLMs) , and advanced Retrieval-Augmented Generation (RAG) techniques to build intelligent, data-driven systems that deliver powerful PR insights. You'll also work on developing agentic workflows that autonomously orchestrate tasks, enabling More ❯

exciting point in our journey, leveraging Generative AI (GenAI) , Large Language Models (LLMs) , and advanced Retrieval-Augmented Generation (RAG) techniques to build intelligent, data-driven systems that deliver powerful PR insights. You'll also work on developing agentic workflows that autonomously orchestrate tasks, enabling More ❯

AI initiatives span categorization, summarization, data analysis, automated content generation, and rich media analysis -leveraging both existing AI/ML tools (LLMs, RAG, embeddings, agentic workflows) and custom solutions. You'll collaborate across teams to build practical, scalable AI solutions - where precision matters. With a "you build it … Select, train, and fine-tune AI models based on need, leveraging appropriate techniques (e.g. LLMs, Retrieval-Augmented Generation (RAG), Vector Databases, Embeddings, Multi-modal AI, Agentic Workflows) (Model Development). Integrate and deploy scalable AI based applications, backend services and APIs (Deployment). Develop More ❯

AI initiatives span categorization, summarization, data analysis, automated content generation, and rich media analysis -leveraging both existing AI/ML tools (LLMs, RAG, embeddings, agentic workflows) and custom solutions. You’ll collaborate across teams to build practical, scalable AI solutions - where precision matters. With a you build it … Select, train, and fine-tune AI models based on need, leveraging appropriate techniques (e.g. LLMs, Retrieval-Augmented Generation (RAG), Vector Databases, Embeddings, Multi-modal AI, Agentic Workflows) (Model Development). Integrate and deploy scalable AI based applications, backend services and APIs (Deployment). Develop More ❯

AI agents, leveraging LLMs, reinforcement learning, vector databases, and autonomous systems . As a key AI strategy leader , you'll define the next-generation consumer experiences , enabling real-time merchant insights , AI-powered Ops automation , and cutting-edge chatbot capabilities . You will collaborate closely with executive leadership … making, and task execution. LLM Fine-Tuning & Enhancement: Adapt foundational models like GPT, Llama, integrating retrieval-augmented generation (RAG), personalization, and continuous improvement loops. Multi-Agent Systems: Implement collaborative AI systems that solve complex challenges in payments and customer interactions. Long-Term AI Memory … Learning, or related field. Experience: 7+ years in AI/ML development, with expertise in Python, TensorFlow, and PyTorch. Core AI Knowledge: LLM Optimization (RAG, fine-tuning, prompt engineering) Vector databases for AI retrieval Multi-agent systems and reinforcement learning Cloud AI deployment (AWS, Azure), inference optimization A More ❯

AI agents, leveraging LLMs, reinforcement learning, vector databases, and autonomous systems . As a key AI strategy leader , you’ll define the next-generation consumer experiences , enabling real-time merchant insights , AI-powered Ops automation , and cutting-edge chatbot capabilities . You will collaborate closely with executive leadership … making, and task execution. LLM Fine-Tuning & Enhancement: Adapt foundational models like GPT, Llama, integrating retrieval-augmented generation (RAG), personalization, and continuous improvement loops. Multi-Agent Systems: Implement collaborative AI systems that solve complex challenges in payments and customer interactions. Long-Term AI Memory … Learning, or related field. Experience: 7+ years in AI/ML development, with expertise in Python, TensorFlow, and PyTorch. Core AI Knowledge: LLM Optimization (RAG, fine-tuning, prompt engineering) Vector databases for AI retrieval Multi-agent systems and reinforcement learning Cloud AI deployment (AWS, Azure), inference optimization A 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 ❯

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 ❯

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 ❯

address specific business challenges. • Work with Large Language Models (LLMs): fine-tuning, prompt engineering, developing Retrieval-Augmented Generation (RAG) systems, and integrating LLM capabilities into applications via APIs. • Process, clean, and analyze large datasets to prepare them for model training and evaluation. • Develop APIs More ❯

AI initiatives span categorization, summarization, data analysis, automated content generation, and rich media analysis - leveraging both existing AI/ML tools (LLMs, RAG, embeddings, agentic workflows) and custom solutions. You'll collaborate across teams to build practical, scalable AI solutions - where precision matters. With a "you build it … Select, train, and fine-tune AI models based on need, leveraging appropriate techniques (e.g. LLMs, Retrieval-Augmented Generation (RAG), Vector Databases, Embeddings, Multi-modal AI, Agentic Workflows) (Model Development). Integrate and deploy scalable AI based applications, backend services and APIs (Deployment). Develop More ❯