76 to 100 of 271 Retrieval-Augmented Generation Jobs in London

problem-solving and technical storytelling abilities. Commitment to ethical AI deployment. Key Skills Advanced Python and backend languages. Expertise in prompt engineering, fine-tuning, RAG, and agentic design. Familiarity with AI tools (GitHub Copilot, ChatGPT, SonarQube, LangChain, etc.). Understanding of observability, security, and compliance in AI systems. Experience with ...

problem-solving and technical storytelling abilities. Commitment to ethical AI deployment. Key Skills Advanced Python and backend languages. Expertise in prompt engineering, fine-tuning, RAG, and agentic design. Familiarity with AI tools (GitHub Copilot, ChatGPT, SonarQube, LangChain, etc.). Understanding of observability, security, and compliance in AI systems. Experience with ...

Doing: Designing, developing, and deploying machine learning and AI models Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines and APIs for AI services ...

Doing: Designing, developing, and deploying machine learning and AI models Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines and APIs for AI services ...

Python and familiarity with deep learning/NLP libraries (LangChain, PyTorch, TensorFlow, HuggingFace Transformers). Experience with building Q&A systems and retrieval-augmented generation pipelines. Knowledge of vector databases or semantic search concepts. Familiarity with cloud AI platforms (AWS Bedrock, Azure OpenAI … deploying AI workloads to Azure Container Apps (ACA), Azure Kubernetes Service (AKS), or serverless functions (Azure Functions) for event-driven agent triggers. Experience implementing RAG using Azure AI Search (vector, semantic, and hybrid search) and OneLake/Microsoft Fabric. Nice to Have Skills Certification: Microsoft Certified: Azure AI Engineer Associate ...

Python and familiarity with deep learning/NLP libraries (LangChain, PyTorch, TensorFlow, HuggingFace Transformers). Experience with building Q&A systems and retrieval-augmented generation pipelines. Knowledge of vector databases or semantic search concepts. Familiarity with cloud AI platforms (AWS Bedrock, Azure OpenAI … deploying AI workloads to Azure Container Apps (ACA), Azure Kubernetes Service (AKS), or serverless functions (Azure Functions) for event-driven agent triggers. Experience implementing RAG using Azure AI Search (vector, semantic, and hybrid search) and OneLake/Microsoft Fabric. Nice to Have Skills Certification: Microsoft Certified: Azure AI Engineer Associate ...

/Vertex AI , including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications , leveraging RAG (Retrieval-Augmented Generation) , agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop … Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems . Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI . Experience with vector databases and retrieval ...

Lead the design, implementation, and fine-tuning of LLMs and generative AI solutions (OpenAI, Anthropic Claude, Gemini, open-source models). Build and optimize RAG pipelines , vector databases, and prompt engineering strategies. Develop AI-powered applications integrating LLMs with APIs, agents, and workflows. Deploy and monitor AI models on cloud ...

production with governance and quality controls. MLOps tooling such as MLflow, Weights & Biases, or DVC. Developing LLM/GenAI applications, including prompt engineering and RAG architectures. Communicating complex findings clearly to technical and non-technical audiences. Nice-to-Haves Advanced LLM techniques: agents, tool use, and agentic workflows. Vector databases ...

/Vertex AI, including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications, leveraging RAG (Retrieval-Augmented Generation), agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop … Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems. Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI. Experience with vector databases and retrieval-based ...

/Vertex AI, including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications, leveraging RAG (Retrieval-Augmented Generation), agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop … Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems. Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI. Experience with vector databases and retrieval-based ...

building GenAI applications using Python Hands-on experience with API development and Microservices architecture and end to end integrations Knowledge of RAG (Retrieval-Augmented Generation ) and ADK, MCP Solid understanding of LLMs, prompt engineering, and graph-based workflows Hands-on experience with API development ...

from experimentation into live systems Experience with MLOps tools (MLflow, Weights & Biases, DVC, or similar) Hands-on exposure to LLM/GenAI applications, including RAG Nice to have: Experience with advanced LLM techniques (e.g. agents, tool use) Familiarity with vector databases and feature stores Experience with Docker, Kubernetes, or Infrastructure ...

from experimentation into live systems Experience with MLOps tools (MLflow, Weights & Biases, DVC, or similar) Hands-on exposure to LLM/GenAI applications, including RAG Nice to have: Experience with advanced LLM techniques (e.g. agents, tool use) Familiarity with vector databases and feature stores Experience with Docker, Kubernetes, or Infrastructure ...

from experimentation into live systems Experience with MLOps tools (MLflow, Weights & Biases, DVC, or similar) Hands-on exposure to LLM/GenAI applications, including RAG Nice to have: Experience with advanced LLM techniques (e.g. agents, tool use) Familiarity with vector databases and feature stores Experience with Docker, Kubernetes, or Infrastructure ...

fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores … ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape ...

fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores … ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape ...

/LLM Engineer (Contract) - RAG Implementation … London (Mostly Remote) - Outside IR35 - Jan Start We're seeking a skilled AI/LLM Engineer to help deliver Retrieval Augmented Generation (RAG) solutions for a major client project in London. This is a hands-on contract role suited to someone with strong implementation ...

shape the organisation’s LLM strategy, conversational AI capabilities, and broader applied AI roadmap. Key Responsibilities Design, build, and enhance LLM-driven tools, including RAG pipelines, embeddings, and prompt engineering. Support and expand the organisation’s chatbot capabilities. Work with unscripted data (text, call transcripts) to define key insights ...

shape the organisation’s LLM strategy, conversational AI capabilities, and broader applied AI roadmap. Key Responsibilities Design, build, and enhance LLM-driven tools, including RAG pipelines, embeddings, and prompt engineering. Support and expand the organisation’s chatbot capabilities. Work with unscripted data (text, call transcripts) to define key insights ...

Proven ability to transition validated models into production-ready systems with appropriate governance Exposure to LLM/Generative AI applications, including prompt engineering and RAG architectures Ability to communicate complex technical concepts clearly to non-technical stakeholders Experience working in cross-functional teams to deliver production solutions Eligibility and willingness ...

Proven ability to transition validated models into production-ready systems with appropriate governance Exposure to LLM/Generative AI applications, including prompt engineering and RAG architectures Ability to communicate complex technical concepts clearly to non-technical stakeholders Experience working in cross-functional teams to deliver production solutions Eligibility and willingness ...

Services industry. Experience with Generative AI, Large Language Models (LLMs), and advanced frameworks like: LangChain, LangGraph, Haystack LlamaIndex, CrewAI, AutoGen, Transformers (Hugging Face) and RAG pipelines. Proven experience in leading teams and managing complex AI projects. Expertise in machine learning, data modelling, and advanced statistical techniques. Strong programming skills ...

Services industry. Experience with Generative AI, Large Language Models (LLMs), and advanced frameworks like: LangChain, LangGraph, Haystack LlamaIndex, CrewAI, AutoGen, Transformers (Hugging Face) and RAG pipelines. Proven experience in leading teams and managing complex AI projects. Expertise in machine learning, data modelling, and advanced statistical techniques. Strong programming skills ...

Architect & Engineer AI Systems: You won’t just call an API; you will build robust processing architectures that leverage off-the-shelf LLMs, RAG pipelines, and context engineering to solve hard problems. You will benchmark these systems rigorously to ensure they actually work, not just "feel" smart. Build the Backend ...