1 to 25 of 102 Remote 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 ❯

to the highest standards. You'll be part of a multidisciplinary team focused on delivering enterprise-grade AI capabilities, including generative AI, agentic AI, LLMs and RAG (retrieval-augmented generation). The AI Engineer will optimise prompts to generative AI models across NiCE's Proactive AI Agent applications, working with several groups in the More ❯

competencies, success in this role hinges on specific, hands-on experience in the following areas: Generative AI Applications: Demonstrable experience designing, building, and deploying applications leveraging Generative AI techniques. RAG Pipelines: Deep understanding and practical experience in developing and optimising Retrieval-Augmented Generation (RAG) pipelines. GenAI Frameworks: Hands-on experience with key frameworks such … APIs (OpenAI, Gemini) and ideally experience handling open-source models. Knowledge Graphs for AI: Experience utilising Knowledge Graphs (Neo4j preferred) as part of AI architectures, as part of modern RAG systems. Highly Desirable: Experience building B2C applications (e.g., chatbots), exploring Agentic AI patterns. What can we offer you? Freedom to help, plan and lead AI/ML architecture decisions in More ❯

work closely with product and domain experts to identify compelling solutions at the intersection of user needs and technical feasibility. Our team is responsible for designing the next generation of risk and fraud investigation software. We own AI innovation for Thomson Reuters' core Risk and Fraud products, including CLEAR , CLEAR Adverse Media , and CLEAR Risk Inform . About … NLP/ML/Knowledge Graph/GenAI systems for commercial applications Practical experience with traditional and state-of-the-art NLP methods, Knowledge Graph algorithms, and GenAI (including RAG and agentic frameworks) Experience writing production code and ensuring well-managed software delivery Demonstrable experience translating complex problems into successful AI applications Outstanding communication, problem-solving, and analysis skills Collaborating More ❯

Python Proficiency : Strong skills with ML frameworks (TensorFlow, PyTorch) and LLM tools (Hugging Face, LangChain, OpenAI APIs) Vector Understanding : Solid knowledge of embeddings, vector databases (Pinecone, Weaviate, FAISS), and RAG pipelines NLP Fundamentals : Text preprocessing, language modelling, and semantic similarity Cloud Experience : AWS ecosystem knowledge (SageMaker, Lambda, etc.) Production Ready : ETL pipelines, version control, Agile methodologies It would be a More ❯

Practical knowledge in data wrangling, handling, processing, integrating, and analyzing large heterogeneous data sets related to drug discovery. LLM Experience: Experience with LLMs (fine-tuning, pretraining, continued pretraining, inference, RAG, and building multi-agent workflows using Llamaindex, Langchain, LangGraph, vector databases, etc.). Production-Grade Models: Significant expertise in building production-grade machine learning models in industry and/or 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 ❯

TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of More ❯

TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of 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 ❯

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 ❯

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 ❯

Shadowing a product owner to map manual processes, then turning those into user stories, threat models, and agent blueprints Designing, building, and deploying agents using orchestration frameworks, vector stores, RAG pipelines, memory systems, and real-time APIs Iterating on prompts, reward strategies, and safety layers through A/B testing against human benchmarks Maintaining a library of reusable agent templates … documentation and enablement materials for the wider engineering and product teams Key Responsibilities Map the AI agent ecosystem: Stay current with developments in LLMs, agent orchestration frameworks, vector databases, RAG patterns, and API-based toolchains. Uncover opportunities: Work with stakeholders to identify high-value use cases for agent-based automation that align with business goals Design agent workflows: Architect secure … experience with cloud-based AI deployment (AWS) Deep understanding of DevOps/MLOps and scalable infrastructure for AI systems Hands-on experience with LLMs, agent orchestration, vector stores and RAG workflows Excellent cross-functional collaboration and communication skills Proven ability to lead and mentor engineers or cross-functional teams Strong problem-solving skills and confidence making decisions amid ambiguity And 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 ❯

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 ❯

with product, data, and engineering teams Mentor peers and bring cutting-edge ML to life in production What You Bring: Strong Python + ML/LLM stack (Transformers, LangChain, RAG, vector DBs) Experience with NLP, embeddings, and cloud tools (AWS preferred) Ability to solve complex problems and ship real impact Passion for AI, autonomy, and collaborative innovation Bonus: 3D, GIS More ❯

Saatchi brand. If this interests you, please keep reading below for more information. Responsibilities • Design, develop and maintain machine learning, deep learning, and AI prototype tools (including LLM and RAG products)• Collaborate with Audience Strategists to solve business problems using data science• Lead and mentor junior data scientists and analysts• Work with Publicis Groupe technology teams to scale prototypes into More ❯