1 to 25 of 270 Retrieval-Augmented Generation Jobs in London

Engineer (RAG) - Contract - 6 months - London - Outside IR35 Contract Length: 6 months Rate: £500 per day - Outside IR35 Location: London/Hybrid working Overview We are seeking an experienced AI Engineer to join on a 6-month contract, supporting the design and development of AI-driven solutions with a strong … improving system reliability, performance, and scalability through continuous improvement. Required Skills & Experience Proven experience in AI Engineering, specifically working with RAG (Retrieval-Augmented Generation) approaches. Strong Python development experience in a production environment. Solid software engineering background, with experience designing and building reliable systems. ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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/ ...

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 ...

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 ...

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 ...

models for production use Build, maintain and enhance prompt engineering strategies and retrieval-augmented generation (RAG) pipelines Collaborate with architects, cloud teams and business stakeholders to ensure secure, scalable and robust deployments Conduct unit and integration testing, troubleshoot issues and support smooth releases into …/CD pipelines and MLOps practices for AI solutions Hands-on experience in model development and fine-tuning Deep expertise in prompt engineering and RAG solution design Performance monitoring and optimisation of AI models Experience developing and deploying APIs using API Gateway Familiarity with Azure cloud services for LLM deployments ...

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 ...