26 to 50 of 300 Retrieval-Augmented Generation Jobs in England

architecture of LLMs. Foundational knowledge of diffusion models for image generation. Can display and present completed project/s using LLMs with a focus on any of the following: RAG, Agentic-RAG, fine-tuning Some experience or familiarity with deploying applications in the Cloud using services such as AWS or Azure. Proven track record in securing web/API applications. More ❯

features in complex business contexts Strong understanding of machine learning algorithms, NLP, and LLMs with demonstrated business application expertise Experience developing AI-powered automation systems, intelligent assistants/copilots, RAG systems, voice interfaces, and computer vision applications (image and video processing) for enterprise environments Knowledge of advanced AI agent frameworks and architectures such as ReAct for building more effective autonomous More ❯

for Information Retrieval, Natural Language Processing and Generative AI to join our AI Experiences team. Our teams are working on exciting initiatives such as: Building and deploying RAG systems, curating data for model training and evaluation, building evaluation systems that facilitate rapid iteration, and understanding how users interact with our systems to identify directions for improvements. Designing tools More ❯

Claude, etc.) • Build and fine-tune SLMs/LLMs using domain-specific data (e.g., ITSM, security, operations) • Design and optimize Retrieval-Augmented Generation (RAG) pipelines with vector DBs (e.g., FAISS, Chroma, Weaviate, Pinecone) • Develop agent-based architectures using LangGraph, AutoGen, CrewAI, or custom frameworks • Integrate AI agents with enterprise tools (ServiceNow, Jira, SAP, Slack More ❯

functional and fast-paced environment. Experimentation Mindset: Passion for testing ideas, building rapidly, and learning from experiments in a structured way. Nice to Have Experience designing RAG (Retrieval-Augmented Generation)/CAG systems using vector databases and hybrid search strategies. Knowledge of LLM vulnerabilities, including adversarial prompting and data poisoning. Experience in designing prompt More ❯

GPT-4.1, o3 and o4-mini along with others from Anthropic and Google Gemini. This places us at the forefront of THE most advanced technological advancements of our generation We're spearheading an unprecedented shift in how the world's asset class is transacted, globally. Legal reasoning is a hard problem and requires some of the smartest and … experiment, and ship new features directly to customers to use Explore and implement advanced concepts such as multi-agent systems, retrieval-augmented generation (RAG), agentic architectures and next generation OCR pipelines Champion quality and reuse across the product and the codebase. Work across the business to ensure the features you develop have More ❯

and US investors . Our founders have delivered cutting-edge AI at world-class research labs and high-growth technology companies. Now, operating in stealth, we apply next-generation agentic AI to overhaul mission-critical enterprise workflows that still depend on error-prone, manual processes. Our vision is to bring these high-value operations into the modern era … event buses (Kafka, Pulsar). Wrangle large, heterogeneous data sets —model, transform, and index multi-modal, multi-terabyte enterprise datasets for advanced AI workloads Develop enterprise-level next generation AI systems with the support of our AI specialists Ship complete customer features - from architecture and code to CI/CD, infra-as-code (Terraform), rollout, and user training. … contract. Thrive in an early-stage, high-ownership environment—prototype today, deploy tomorrow, iterate next week. Bonus Points Experience deploying or consuming LLM-powered services (OpenAI, open-source models, RAG, vector stores) can be a bonus. However, we consider many great candidates without previous AI experience. What we're offering: Base salary from £115,000 - £135,000. .. plus meaningful More ❯

and US investors . Our founders have delivered cutting-edge AI at world-class research labs and high-growth technology companies. Now, operating in stealth, we apply next-generation agentic AI to overhaul mission-critical enterprise workflows that still depend on error-prone, manual processes. Our vision is to bring these high-value operations into the modern era … event buses (Kafka, Pulsar). Wrangle large, heterogeneous data sets —model, transform, and index multi-modal, multi-terabyte enterprise datasets for advanced AI workloads Develop enterprise-level next generation AI systems with the support of our AI specialists Ship complete customer features - from architecture and code to CI/CD, infra-as-code (Terraform), rollout, and user training. … contract. Thrive in an early-stage, high-ownership environment—prototype today, deploy tomorrow, iterate next week. Bonus Points Experience deploying or consuming LLM-powered services (OpenAI, open-source models, RAG, vector stores) can be a bonus. However, we consider many great candidates without previous AI experience. What we're offering: Base salary from £115,000 - £135,000. .. plus meaningful More ❯

and US investors . Our founders have delivered cutting-edge AI at world-class research labs and high-growth technology companies. Now, operating in stealth, we apply next-generation agentic AI to overhaul mission-critical enterprise workflows that still depend on error-prone, manual processes. Our vision is to bring these high-value operations into the modern era … event buses (Kafka, Pulsar). Wrangle large, heterogeneous data sets —model, transform, and index multi-modal, multi-terabyte enterprise datasets for advanced AI workloads Develop enterprise-level next generation AI systems with the support of our AI specialists Ship complete customer features - from architecture and code to CI/CD, infra-as-code (Terraform), rollout, and user training. … contract. Thrive in an early-stage, high-ownership environment—prototype today, deploy tomorrow, iterate next week. Bonus Points Experience deploying or consuming LLM-powered services (OpenAI, open-source models, RAG, vector stores) can be a bonus. However, we consider many great candidates without previous AI experience. What we're offering: Base salary from £115,000 - £135,000. .. plus meaningful More ❯

platform used by thousands. This is a hands-on engineering role where you'll design, deploy, and optimise systems that power real-world use cases - from LLM deployments to RAG pipelines and NLP automation. What you'll do: Maintain and improve AI codebases for performance and reliability Deploy LLMs using frameworks like SGLang, TGI, vLLM Build RAG pipelines, embedding, reranking More ❯

Fluent in English (written and spoken). (For senior candidates) Ability to manage projects and lead teams. Good to Have Knowledge or hands-on experience with Generative AI, LLMs, RAG, prompt engineering, and information retrieval. Familiarity with credit-related topics and regulatory frameworks like Basel and IFRS 9. Why Join Us? Work on impactful projects shaping the future of financial More ❯

varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term … cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI innovation, where your work will directly shape how next-generation systems interact, reason, and assist. More ❯

varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term … cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI innovation, where your work will directly shape how next-generation systems interact, reason, and assist. More ❯

varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term … cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI innovation, where your work will directly shape how next-generation systems interact, reason, and assist. More ❯

lead the development of advanced 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, key industry stakeholders, and regulatory … capable of autonomous learning, decision-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 & Personalization: Develop solutions to enhance … in Computer Science, AI, Machine 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 snippet of what you'll More ❯

professional development! Requirements: Strong skills in Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies Experience with Cloud platforms – ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around £60,000 depending upon experience More ❯

professional development! Requirements: Strong skills in Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies Experience with Cloud platforms – ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around £60,000 depending upon experience More ❯

healthcare and cutting-edge LLM technology, shipping fast and solving meaningful problems every day. What You’ll Own Architect and develop backend microservices (Python/FastAPI) that power our RAG pipelines and analytics Build scalable infrastructure for retrieval and vector search (PGVector, Pinecone, Weaviate) Design evaluation frameworks to improve search accuracy and reduce hallucinations Deploy and manage services … LlamaIndex What We’re Looking For 5+ years building production-grade backend systems (preferably in Python) Strong background in search, recommender systems, or ML infrastructure at scale Experience with RAG architectures, embeddings, and vector search Confidence working across GCP (or AWS/Azure) and infrastructure-as-code Familiarity with observability, performance tuning, and secure data practices A growth mindset, startup More ❯

healthcare and cutting-edge LLM technology, shipping fast and solving meaningful problems every day. What You’ll Own Architect and develop backend microservices (Python/FastAPI) that power our RAG pipelines and analytics Build scalable infrastructure for retrieval and vector search (PGVector, Pinecone, Weaviate) Design evaluation frameworks to improve search accuracy and reduce hallucinations Deploy and manage services … LlamaIndex What We’re Looking For 5+ years building production-grade backend systems (preferably in Python) Strong background in search, recommender systems, or ML infrastructure at scale Experience with RAG architectures, embeddings, and vector search Confidence working across GCP (or AWS/Azure) and infrastructure-as-code Familiarity with observability, performance tuning, and secure data practices A growth mindset, startup More ❯

healthcare and cutting-edge LLM technology, shipping fast and solving meaningful problems every day. What You’ll Own Architect and develop backend microservices (Python/FastAPI) that power our RAG pipelines and analytics Build scalable infrastructure for retrieval and vector search (PGVector, Pinecone, Weaviate) Design evaluation frameworks to improve search accuracy and reduce hallucinations Deploy and manage services … LlamaIndex What We’re Looking For 5+ years building production-grade backend systems (preferably in Python) Strong background in search, recommender systems, or ML infrastructure at scale Experience with RAG architectures, embeddings, and vector search Confidence working across GCP (or AWS/Azure) and infrastructure-as-code Familiarity with observability, performance tuning, and secure data practices A growth mindset, startup More ❯

LLM pipelines, ensuring versioning, monitoring, and adherence to best practices. Drive integration of external knowledge bases and retrieval systems to augment LLM capabilities. Research and Development: Develop RAG architectures, organize complex domain-specific data (e.g., vector databases, knowledge graphs), and implement knowledge extraction. Benchmark and tune state-of-the-art LLMs for performance and cost efficiency. Incorporate trends … least 2 years in a senior or lead role. Proven expertise with modern LLMs in production. Leadership skills: Proven leadership in agile environments, strong communication, mentoring abilities. LLM and RAG expertise: Building RAG architectures, integrating vector and graph databases. Transformer and LLM architectures: Experience with GPT-4, Claude, Gemini, Llama, Falcon, Mistral. Model performance and optimization: Fine-tuning and optimizing More ❯

tier third-party vendors, platforms, and internal tech teams. Enable Cross-Functional Success: Work closely with IT, Big Data, Security, Digital, and Business Units. Innovate with AI: Leverage LLMs, RAG, MLOps, and cloud-native tools to build scalable, secure solutions. Ensure Governance: Align with enterprise standards, responsible AI practices, and compliance frameworks. Deliver Measurable Impact: Define success metrics and ensure … is realized at every stage. Key Skills and Experience: Proven experience architecting AI/ML or GenAI solutions in complex, enterprise environments. Hands-on expertise with LLMs, NLP, MLOps, RAG pipelines, APIs, and real-time data systems. Strong track record in networks, telecom, or customer experience domains (preferred). Proficiency in cloud platforms like GCP, AWS, or Azure; plus tools More ❯

tier third-party vendors, platforms, and internal tech teams. Enable Cross-Functional Success: Work closely with IT, Big Data, Security, Digital, and Business Units. Innovate with AI: Leverage LLMs, RAG, MLOps, and cloud-native tools to build scalable, secure solutions. Ensure Governance: Align with enterprise standards, responsible AI practices, and compliance frameworks. Deliver Measurable Impact: Define success metrics and ensure … is realized at every stage. Key Skills and Experience: Proven experience architecting AI/ML or GenAI solutions in complex, enterprise environments. Hands-on expertise with LLMs, NLP, MLOps, RAG pipelines, APIs, and real-time data systems. Strong track record in networks, telecom, or customer experience domains (preferred). Proficiency in cloud platforms like GCP, AWS, or Azure; plus tools More ❯

internal AI Centre of Excellence. Act as the primary AI representative in leadership and product discussions. Deliver generative AI solutions - Design and deploy GenAI applications (e.g. virtual assistants, copilots, RAG systems) Set up scalable LLMOps pipelines: model evaluation, versioning, and governance. Monitor developments in the GenAI landscape and evaluate adoption paths. Support machine learning projects - Collaborate with ML Engineers on … analysis. Help shape the future team structure, tool stack, and hiring strategy. About You Must-Haves Experience delivering production-ready GenAI solutions Solid grasp of LLMs, prompt engineering, and RAG workflows Familiarity with MLOps practices and deployment of classical ML models Competence in statistical modelling and A/B testing frameworks Proficiency in Python and at least one other programming More ❯

of experience Experience in Knowledge Graphs or Large Document Search Experience with traditional ML models and feature engineering. Strong Experience with fine tuning, modelling and deploying LLMs - experience with RAG, IR, NER etc would also be very beneficial Strong programming skills (e.g., Python) and experience with modern ML frameworks (e.g., PyTorch, TensorFlow, LangChain). Collaborating with other Researchers, Product, Engineering More ❯