1 to 25 of 132 Permanent Retrieval-Augmented Generation Jobs in London

intelligence. Build robust APIs, microservices, and data pipelines to power intelligent, data-driven tools. Develop retrieval-augmented generation (RAG) systems using vector databases for contextual AI. Set the technical direction for backend and AI integration best practices. Partner with cross-functional teams to identify … outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and comprehensive ...

intelligence. Build robust APIs, microservices, and data pipelines to power intelligent, data-driven tools. Develop retrieval-augmented generation (RAG) systems using vector databases for contextual AI. Set the technical direction for backend and AI integration best practices. Partner with cross-functional teams to identify … outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and comprehensive ...

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 ...

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 ...

techniques. Drive innovation in Large Language Models (LLMs), Generative AI, and Agentic AI—pioneering new applications such as enhanced personalization, lead qualification, content generation, and workflow automation. Own the end-to-end ML lifecycle: from hypothesis generation, experimentation, evaluation, and explainability, to scalable deployment in production … libraries (PyTorch or TensorFlow). Hands-on experience with LLMs, prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) pipelines. Experience integrating ML models via APIs and embedding AI in enterprise systems. Deep knowledge of cloud platforms (AWS/GCP/Azure) and containerized ...

techniques. Drive innovation in Large Language Models (LLMs), Generative AI, and Agentic AI—pioneering new applications such as enhanced personalization, lead qualification, content generation, and workflow automation. Own the end-to-end ML lifecycle: from hypothesis generation, experimentation, evaluation, and explainability, to scalable deployment in production … libraries (PyTorch or TensorFlow). Hands-on experience with LLMs, prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) pipelines. Experience integrating ML models via APIs and embedding AI in enterprise systems. Deep knowledge of cloud platforms (AWS/GCP/Azure) and containerized ...

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. ...

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 ...

workloads using languages such as Python, Golang, or Node.js. Productionize ML/GenAI solutions, including: Retrieval-Augmented Generation (RAG) for support, content, and internal tools Recommendation and ranking services Classification, quality scoring, and enrichment pipelines Implement and evolve the AI/ML platform, including … cross-functional Agile teams. Hands-on experience with AI/ML or GenAI in production, such as: Fine-tuning or integrating transformer models Building RAG pipelines and semantic search Working with vector databases (e.g., Pinecone, Weaviate, Milvus, OpenSearch, etc.) Self-motivated and proactive, able to work independently where needed while ...

workloads using languages such as Python, Golang, or Node.js. Productionize ML/GenAI solutions, including: Retrieval-Augmented Generation (RAG) for support, content, and internal tools Recommendation and ranking services Classification, quality scoring, and enrichment pipelines Implement and evolve the AI/ML platform, including … cross-functional Agile teams. Hands-on experience with AI/ML or GenAI in production, such as: Fine-tuning or integrating transformer models Building RAG pipelines and semantic search Working with vector databases (e.g., Pinecone, Weaviate, Milvus, OpenSearch, etc.) Self-motivated and proactive, able to work independently where needed while ...

digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skills and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People … experience with SAP AI Core, Generative AI Hub, and SAP HANA Cloud Vector Engine (for Retrieval-Augmented Generation, RAG). Proven ability to embed AI and advanced analytics into SAP business processes, leveraging SAP’s Business AI suite and integrating external LLMs (e.g., OpenAI ...

digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skills and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People … experience with SAP AI Core, Generative AI Hub, and SAP HANA Cloud Vector Engine (for Retrieval-Augmented Generation, RAG). Proven ability to embed AI and advanced analytics into SAP business processes, leveraging SAP’s Business AI suite and integrating external LLMs (e.g., OpenAI ...

Have Experience with multi-modal AI (text, image, audio). Familiarity with vector databases and retrieval-augmented generation (RAG) . Background in enterprise architecture frameworks . Why Join? Work on innovative AI projects shaping the future of enterprise solutions. Collaborate with a high-performing ...

Have Experience with multi-modal AI (text, image, audio). Familiarity with vector databases and retrieval-augmented generation (RAG) . Background in enterprise architecture frameworks . Why Join? Work on innovative AI projects shaping the future of enterprise solutions. Collaborate with a high-performing ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents. Scale existing POCs to production-ready solutions for customer use. Design and develop Full Stack applications for both GenAI and non-GenAI ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents. Scale existing POCs to production-ready solutions for customer use. Design and develop Full Stack applications for both GenAI and non-GenAI ...

context and tool interfaces for agents. LLM integration patterns, including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). ...

context and tool interfaces for agents. LLM integration patterns, including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents. Scale existing POCs to production-ready solutions for customer use. Design and develop Full Stack applications for both GenAI and non-GenAI ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents. Scale existing POCs to production-ready solutions for customer use. Design and develop Full Stack applications for both GenAI and non-GenAI ...