1 to 25 of 248 Retrieval-Augmented Generation Jobs in London

focused on building the intelligence layer of advanced AI products. You will design and implement Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and robust evaluation frameworks that ensure AI systems are accurate and aligned with real-world business needs. Reporting to the Director … with AI Platform Engineering to ensure solutions are scalable, maintainable, and production ready. Design, build, and train production-grade generative AI systems. Implement robust RAG pipelines that effectively leverage proprietary and domain-specific content. Develop agentic and workflow-based AI patterns with a focus on determinism, quality, and maintainability. Apply ...

focused on building the intelligence layer of advanced AI products. You will design and implement Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and robust evaluation frameworks that ensure AI systems are accurate and aligned with real-world business needs. Reporting to the Director … with AI Platform Engineering to ensure solutions are scalable, maintainable, and production ready. Design, build, and train production-grade generative AI systems. Implement robust RAG pipelines that effectively leverage proprietary and domain-specific content. Develop agentic and workflow-based AI patterns with a focus on determinism, quality, and maintainability. Apply ...

focused on building the intelligence layer of advanced AI products. You will design and implement Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and robust evaluation frameworks that ensure AI systems are accurate and aligned with real-world business needs. Reporting to the Director … with AI Platform Engineering to ensure solutions are scalable, maintainable, and production ready. Design, build, and train production-grade generative AI systems. Implement robust RAG pipelines that effectively leverage proprietary and domain-specific content. Develop agentic and workflow-based AI patterns with a focus on determinism, quality, and maintainability. Apply ...

optimise pipelines for data collection, preprocessing, and model evaluation. Collaborate with product engineers to deploy models into scalable production systems. Experiment with prompt engineering, RAG architectures, and multimodal models. Contribute to internal tools for monitoring, testing, and improving AI performance. Stay on the edge of ML/AI research … Intelligence, Deep Learning, NLP, Natural Language Processing, Large Language Models, Generative AI, GenAI, Neural Networks, PyTorch, TensorFlow, Hugging Face, OpenAI, LangChain, RAG, Retrieval-Augmented Generation, Python, Data Science, AI Research, MLOps, Data Pipelines, Prompt Engineering, Model Fine-Tuning, Cloud Computing, AWS, Azure, Google Cloud ...

will leverage managed AI services across GCP and Azure to deliver features like semantic search, retrieval-augmented generation (RAG), and intelligent data enrichment. Working closely with Data and ML Engineers, you will define patterns, select technologies, and ensure our solutions are secure, performant … Search with embeddings. Cost & Performance : Establish strategies for latency optimization and cost control across clouds. AI Enablement & Delivery RAG System Design : Implement retrieval-augmented generation patterns for small, volatile data chunks; ensure grounding and factuality. Evaluation & Observability : Define quality metrics (precision/recall, groundedness ...

will leverage managed AI services across GCP and Azure to deliver features like semantic search, retrieval-augmented generation (RAG), and intelligent data enrichment. Working closely with Data and ML Engineers, you will define patterns, select technologies, and ensure our solutions are secure, performant … Search with embeddings. Cost & Performance : Establish strategies for latency optimization and cost control across clouds. AI Enablement & Delivery RAG System Design : Implement retrieval-augmented generation patterns for small, volatile data chunks; ensure grounding and factuality. Evaluation & Observability : Define quality metrics (precision/recall, groundedness ...

implement robust, goal-driven AI agents using leading frameworks like LangChain, LangGraph, and the Google Agent Development Kit (ADK). Develop and Evaluate RAG Pipelines: Engineer and optimize end-to-end Retrieval-Augmented Generation (RAG) systems, including data ingestion, chunking strategies, and implementing rigorous … Prompt Engineering and hands-on experience with model fine-tuning techniques including PEFT and QLoRA. Proven experience with models like Gemini, and Llama 3. RAG & Vector Databases: Deep expertise in RAG architecture and evaluation metrics. Proven experience with Vector Databases such as Milvus, Pinecone, or Chroma. Software & Cloud Engineering: Programming ...

implement robust, goal-driven AI agents using leading frameworks like LangChain, LangGraph, and the Google Agent Development Kit (ADK). Develop and Evaluate RAG Pipelines: Engineer and optimize end-to-end Retrieval-Augmented Generation (RAG) systems, including data ingestion, chunking strategies, and implementing rigorous … Prompt Engineering and hands-on experience with model fine-tuning techniques including PEFT and QLoRA. Proven experience with models like Gemini, and Llama 3. RAG & Vector Databases: Deep expertise in RAG architecture and evaluation metrics. Proven experience with Vector Databases such as Milvus, Pinecone, or Chroma. Software & Cloud Engineering: Programming ...

Experience with: AWS: boto3, Bedrock, SageMaker, Lambda, S3, EC2 Azure: Azure OpenAI Service, Cosmos DB Retrieval-Augmented Generation (RAG), Graph RAG Embedding models and LLM training fundamentals Damia Group Limited acts as an employment agency for permanent recruitment and employment business for the supply ...

field. Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection). Strong Python skills with a grounding in software engineering best practices ...

Level: Junior–Mid Overview: As a Developer Advocate focused on AI/GenAI, you will empower AI builders with practical LLM/RAG samples, vector search demos, and hands-on tutorials. You'll foster engagement and growth in the AI developer community while ensuring GitHub advocacy repositories remain organized, discoverable … date. Key Responsibilities: Build AI/GenAI sample applications, including prompt pipelines, embeddings, retrieval-augmented generation (RAG), and evaluation/reference implementations. Maintain GitHub repositories and automation for AI assets; standardize repo structure, documentation, and contribution models. Produce step-by-step tutorials, quickstarts ...

Level: Junior–Mid Overview: As a Developer Advocate focused on AI/GenAI, you will empower AI builders with practical LLM/RAG samples, vector search demos, and hands-on tutorials. You'll foster engagement and growth in the AI developer community while ensuring GitHub advocacy repositories remain organized, discoverable … date. Key Responsibilities: Build AI/GenAI sample applications, including prompt pipelines, embeddings, retrieval-augmented generation (RAG), and evaluation/reference implementations. Maintain GitHub repositories and automation for AI assets; standardize repo structure, documentation, and contribution models. Produce step-by-step tutorials, quickstarts ...

design, build, and deliver next-generation AI systems. You will work across LLMs, retrieval-augmented generation (RAG), and modern agent frameworks to transform large, unstructured data into meaningful insights and production-ready capabilities. This is a hands-on role within a growing … entity extraction, and intelligent automation. Design scalable data and streaming pipelines capable of handling large, heterogeneous datasets. Build and optimize vector search, embeddings, and RAG systems to support high-quality retrieval. Deliver production-ready APIs, services, and model inference systems. Manage deployment, monitoring, observability, and continual improvement of ML models. ...

design, build, and deliver next-generation AI systems. You will work across LLMs, retrieval-augmented generation (RAG), and modern agent frameworks to transform large, unstructured data into meaningful insights and production-ready capabilities. This is a hands-on role within a growing … entity extraction, and intelligent automation. Design scalable data and streaming pipelines capable of handling large, heterogeneous datasets. Build and optimize vector search, embeddings, and RAG systems to support high-quality retrieval. Deliver production-ready APIs, services, and model inference systems. Manage deployment, monitoring, observability, and continual improvement of ML models. ...

design, build, and deliver next-generation AI systems. You will work across LLMs, retrieval-augmented generation (RAG), and modern agent frameworks to transform large, unstructured data into meaningful insights and production-ready capabilities. This is a hands-on role within a growing … entity extraction, and intelligent automation. Design scalable data and streaming pipelines capable of handling large, heterogeneous datasets. Build and optimize vector search, embeddings, and RAG systems to support high-quality retrieval. Deliver production-ready APIs, services, and model inference systems. Manage deployment, monitoring, observability, and continual improvement of ML models. ...

Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js. Collaborate … LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g. ...

Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js. Collaborate … LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g. ...

Data Version Control Practical experience building LLM/GenAI applications, including prompt engineering and retrieval-augmented generation (RAG) Familiarity with LLMOps frameworks such as LangChain, LangSmith or LangGraph Understanding of model validation, evaluation techniques and production monitoring Experience working in cross-functional teams from ...

that power all internal GenAI product squads. You will be instrumental in designing and implementing our award winning Generative AI Platform Model Orchestration Layer, RAG infrastructure, communications layer, agentic layer and centralised governance/safety guardrails etc. This is a hybrid role, typically working 1 day per week … access to LLMs and other generative models. Engineer and maintain production-ready Vector Database and Retrieval-Augmented Generation (RAG) infrastructure, including high-throughput indexing pipelines and efficient retrieval strategies for enterprise data. Develop and manage a standardised, secure Agent Framework/ ...

help drive innovation across cutting-edge AI initiatives — from chatbots and voice assistants to advanced retrieval-augmented generation (RAG) systems and agentic workflows. The Role You’ll work closely with the AI Engineering and Data Science teams to: Develop and prototype AI-driven solutions … across customer-facing and internal applications. Build and optimise LLM-based assistants , RAG pipelines , and agentic AI workflows . Collaborate on the architecture and deployment of scalable AI solutions (with support from engineering). Partner with stakeholders to translate business needs into practical, intelligent systems. Mentor junior team members ...

help drive innovation across cutting-edge AI initiatives — from chatbots and voice assistants to advanced retrieval-augmented generation (RAG) systems and agentic workflows. The Role You’ll work closely with the AI Engineering and Data Science teams to: Develop and prototype AI-driven solutions … across customer-facing and internal applications. Build and optimise LLM-based assistants , RAG pipelines , and agentic AI workflows . Collaborate on the architecture and deployment of scalable AI solutions (with support from engineering). Partner with stakeholders to translate business needs into practical, intelligent systems. Mentor junior team members ...

help drive innovation across cutting-edge AI initiatives — from chatbots and voice assistants to advanced retrieval-augmented generation (RAG) systems and agentic workflows. The Role You’ll work closely with the AI Engineering and Data Science teams to: Develop and prototype AI-driven solutions … across customer-facing and internal applications. Build and optimise LLM-based assistants , RAG pipelines , and agentic AI workflows . Collaborate on the architecture and deployment of scalable AI solutions (with support from engineering). Partner with stakeholders to translate business needs into practical, intelligent systems. Mentor junior team members ...

Strands Agents, LangGraph, or similar LLM integration and fine-tuning (Claude, GPT-4, or equivalent) Strong prompt engineering skills, including chain-of-thought reasoning RAG & Knowledge Systems Implementation of Retrieval-Augmented Generation (RAG) pipelines Experience with vector databases such as CockroachDB, Pinecone, or similar ...

Strands Agents, LangGraph, or similar LLM integration and fine-tuning (Claude, GPT-4, or equivalent) Strong prompt engineering skills, including chain-of-thought reasoning RAG & Knowledge Systems Implementation of Retrieval-Augmented Generation (RAG) pipelines Experience with vector databases such as CockroachDB, Pinecone, or similar ...

Responsibilities: Design, build, and deploy Large Language Model (LLM)-driven applications into production Develop retrieval-augmented generation (RAG) systems for real-time insights from performance and wearable data Optimise and fine-tune LLMs for efficiency, scalability, and accuracy in production environments Build and maintain … software engineering fundamentals Proven experience working with LLMs in production (fine-tuning, prompt engineering, or API integrations) Proficiency in Python Experience designing and deploying RAG pipelines (vector databases, embeddings, retrieval optimisation) Academic Excellence: BSc or MSc in Computer Science, AI, Data Science, or related technical field from ...