76 to 100 of 962 Retrieval-Augmented Generation Jobs in England

Azure environment.Define technical standards and best practices for developing advanced Generative AI applications, encompassing complex Retrieval-Augmented Generation (RAG) architectures, prompt and context engineering, and Large Language Model (LLM) integration strategies.Architect innovative Agentic AI systems, establishing frameworks for orchestration, memory management, and robust evaluation.Shape … within Azure environments, with a focus on technical escalation and resolution.Expertise in establishing technical standards and best practices for advanced Generative AI applications, encompassing RAG architectures, prompt engineering, and LLM integration strategies.Experience in architecting and developing Agentic AI systems, including frameworks for orchestration, memory management, and performance evaluation.Advanced knowledge ...

Azure environment.Define technical standards and best practices for developing advanced Generative AI applications, encompassing complex Retrieval-Augmented Generation (RAG) architectures, prompt and context engineering, and Large Language Model (LLM) integration strategies.Architect innovative Agentic AI systems, establishing frameworks for orchestration, memory management, and robust evaluation.Shape … within Azure environments, with a focus on technical escalation and resolution.Expertise in establishing technical standards and best practices for advanced Generative AI applications, encompassing RAG architectures, prompt engineering, and LLM integration strategies.Experience in architecting and developing Agentic AI systems, including frameworks for orchestration, memory management, and performance evaluation.Advanced knowledge ...

Azure environment.Define technical standards and best practices for developing advanced Generative AI applications, encompassing complex Retrieval-Augmented Generation (RAG) architectures, prompt and context engineering, and Large Language Model (LLM) integration strategies.Architect innovative Agentic AI systems, establishing frameworks for orchestration, memory management, and robust evaluation.Shape … within Azure environments, with a focus on technical escalation and resolution.Expertise in establishing technical standards and best practices for advanced Generative AI applications, encompassing RAG architectures, prompt engineering, and LLM integration strategies.Experience in architecting and developing Agentic AI systems, including frameworks for orchestration, memory management, and performance evaluation.Advanced knowledge ...

environment. Define technical standards and best practices for developing advanced Generative AI applications, encompassing complex Retrieval-Augmented Generation (RAG) architectures, prompt and context engineering, and Large Language Model (LLM) integration strategies. Architect innovative Agentic AI systems, establishing frameworks for orchestration, memory management, and robust … Azure environments, with a focus on technical escalation and resolution. Expertise in establishing technical standards and best practices for advanced Generative AI applications, encompassing RAG architectures, prompt engineering, and LLM integration strategies. Experience in architecting and developing Agentic AI systems, including frameworks for orchestration, memory management, and performance evaluation. Advanced ...

environment. Define technical standards and best practices for developing advanced Generative AI applications, encompassing complex Retrieval-Augmented Generation (RAG) architectures, prompt and context engineering, and Large Language Model (LLM) integration strategies. Architect innovative Agentic AI systems, establishing frameworks for orchestration, memory management, and robust … Azure environments, with a focus on technical escalation and resolution. Expertise in establishing technical standards and best practices for advanced Generative AI applications, encompassing RAG architectures, prompt engineering, and LLM integration strategies. Experience in architecting and developing Agentic AI systems, including frameworks for orchestration, memory management, and performance evaluation. Advanced ...

environment. Define technical standards and best practices for developing advanced Generative AI applications, encompassing complex Retrieval-Augmented Generation (RAG) architectures, prompt and context engineering, and Large Language Model (LLM) integration strategies. Architect innovative Agentic AI systems, establishing frameworks for orchestration, memory management, and robust … Azure environments, with a focus on technical escalation and resolution. Expertise in establishing technical standards and best practices for advanced Generative AI applications, encompassing RAG architectures, prompt engineering, and LLM integration strategies. Experience in architecting and developing Agentic AI systems, including frameworks for orchestration, memory management, and performance evaluation. Advanced ...

pipelines, distributed training frameworks, inference/serving platforms, MLOps/LLMOps tooling, vector databases, and retrieval-augmented generation (RAG) and agentic architectures. Define and AI governance frameworks covering model risk management, responsible AI, data lineage, bias/fairness testing, explainability, and regulatory alignment … Kubeflow, MLflow, and at least one hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI). Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks (LangChain, LangGraph, Semantic Kernel). Data pipelines: data lake/lakehouse architectures, ETL/ ...

hands-on AI & Data Engineer to design, build and productionise AI agents, automation solutions, Retrieval-Augmented Generation (RAG) capabilities and data products supporting Balance Sheet Modelling . The role will work closely with business, architecture and technology teams to translate business use cases into … Umbrella. Remote First Working - Travel to local site when required. Key Responsibilities Design, develop and deploy production-ready AI agents and agentic workflows. Build RAG solutions, integrating Large Language Models (LLMs) with enterprise data and knowledge sources. Apply prompt engineering techniques to improve the accuracy, reliability and effectiveness ...

hands-on AI & Data Engineer to design, build and productionise AI agents, automation solutions, Retrieval-Augmented Generation (RAG) capabilities and data products supporting Balance Sheet Modelling.The role will work closely with business, architecture and technology teams to translate business use cases into scalable, secure … role will be Via Umbrella.Remote First Working - Travel to local site when required.Key ResponsibilitiesDesign, develop and deploy production-ready AI agents and agentic workflows.Build RAG solutions, integrating Large Language Models (LLMs) with enterprise data and knowledge sources.Apply prompt engineering techniques to improve the accuracy, reliability and effectiveness of AI solutions.Translate ...

scalable AI solutions. Key responsibilities will include: Leading the technical design and delivery of Generative AI and Machine Learning solutions Designing enterprise-grade LLM, RAG and AI agent architectures Building and integrating conversational, voice-to-text and speech-based AI solutions Developing AI applications using commercial and open-source models … candidates with experience across: Generative AI Large Language Models (LLMs) Machine Learning Deep Learning Retrieval-Augmented Generation (RAG) AI Agents and Agentic AI Multi-agent systems Voice AI Speech-to-text/text-to-speech ElevenLabs AWS Bedrock Amazon SageMaker Google Cloud Platform ...

/CD practices.Experience working with cloud platforms and cloud-native deployments.Practical understanding of prompt engineering, retrieval-augmented generation (RAG), agent orchestration and AI evaluation techniques.Experience integrating APIs, data platforms and enterprise systems.Excellent analytical, problem-solving and troubleshooting skills.Experience with Microsoft Copilot Studio, Azure ...

practices. Experience working with cloud platforms and cloud-native deployments. Practical understanding of prompt engineering, retrieval-augmented generation (RAG), agent orchestration and AI evaluation techniques. Experience integrating APIs, data platforms and enterprise systems. Excellent analytical, problem-solving and troubleshooting skills. Experience with Microsoft Copilot ...

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 ...

Biases or Data Version ControlPractical experience building LLM/GenAI applications, including prompt engineering and retrieval-augmented generation (RAG)Familiarity with LLMOps frameworks such as LangChain, LangSmith or LangGraphUnderstanding of model validation, evaluation techniques and production monitoringExperience working in cross-functional teams from problem ...

deployment of GenAI solutions, including LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG) for enterprise use cases. The ideal candidate has a strong foundation in machine learning and NLP, with hands‐on experience in modern GenAI tools and frameworks ...

architecture strategy and roadmap. Build scalable AI/ML and Agentic AI platforms spanning LLMs, retrieval-augmented generation (RAG), embeddings and semantic search. Lead on deployment, governance and integration patterns, advise clients on platform capability and implementation strategy, and partner with engineering, data, DevOps … business teams to deliver end-to-end solutions.**Tech environment**Python, LLMs (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes and GPU infrastructure.**What we're looking for**Proven enterprise AI or ML architecture design, strong cloud ...

international Bank. This is an excellent opportunity for an AI Engineer with strong hands-on experience across Generative AI, Large Language Models (LLMs), RAG, GitHub Copilot and Agentic AI. You will be building real-world AI applications, intelligent assistants, copilots and automation solutions while helping engineering teams adopt the latest … Generative AI and LLM-powered applications Develop AI assistants, copilots and intelligent automation solutions Build Retrieval-Augmented Generation (RAG) applications Work with vector databases and enterprise knowledge sources Integrate LLM and AI services through APIs and cloud architectures Develop and optimise prompts for enterprise ...

doDesign and build AI-enabled platforms and intelligent workflows using large language models (LLMs), retrieval-augmented generation (RAG) pipelines and embedding models. Develop scalable backend services and AI integrations, working closely with engineering, architecture and business teams, and support deployment, governance and operational rollout … data infrastructure exposure, plus experience in Financial Services or another regulated industry, is essential.Tech skills include Python, SQL, LLM development (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, FastAPI, and AWS, Azure, GCP or Databricks. CI/CD, MLOps and LLMOps familiarity expected. Strong communication ...

existing business systems and platforms using REST APIs and cloud-native architectures. Build and optimise Retrieval-Augmented Generation (RAG) solutions, embeddings, and vector database implementations. Develop AI Agents and Multi-Agent Systems to automate complex business processes. Apply prompt engineering and context engineering techniques … business stakeholders to drive AI adoption and innovation. Required Experience: Strong background in Generative AI, LLMs, NLP, and AI Engineering. Hands-on experience with RAG, embeddings, and vector databases. Proven experience developing AI Agents and agentic workflows. Proficient in Python, SQL, and API integration. Familiarity with cloud platforms such ...

using Azure AI Foundry, Copilot Studio, Databricks Mosaic AI and MLflow. Building, optimising and evaluating Retrieval-Augmented Generation (RAG) solutions using prompt engineering and embedding models. Designing and deploying AI agents using frameworks including LangChain, LangGraph and AutoGen. Delivering production-ready GenAI applications … Delta Lake, Unity Catalog, DLT and MLflow. Deep knowledge of Large Language Models including GPT, Llama, Claude and Mistral. Experience building and deploying GenAI, RAG and Agentic AI solutions in enterprise environments. Strong programming skills in Python, SQL and/or Scala. Experience with Azure cloud technologies including Azure OpenAI ...

using Azure AI Foundry, Copilot Studio, Databricks Mosaic AI and MLflow. Building, optimising and evaluating Retrieval-Augmented Generation (RAG) solutions using prompt engineering and embedding models. Designing and deploying AI agents using frameworks including LangChain, LangGraph and AutoGen. Delivering production-ready GenAI applications … Delta Lake, Unity Catalog, DLT and MLflow. Deep knowledge of Large Language Models including GPT, Llama, Claude and Mistral. Experience building and deploying GenAI, RAG and Agentic AI solutions in enterprise environments. Strong programming skills in Python, SQL and/or Scala. Experience with Azure cloud technologies including Azure OpenAI ...

using Azure AI Foundry, Copilot Studio, Databricks Mosaic AI and MLflow. Building, optimising and evaluating Retrieval-Augmented Generation (RAG) solutions using prompt engineering and embedding models. Designing and deploying AI agents using frameworks including LangChain, LangGraph and AutoGen. Delivering production-ready GenAI applications … Delta Lake, Unity Catalog, DLT and MLflow. Deep knowledge of Large Language Models including GPT, Llama, Claude and Mistral. Experience building and deploying GenAI, RAG and Agentic AI solutions in enterprise environments. Strong programming skills in Python, SQL and/or Scala. Experience with Azure cloud technologies including Azure OpenAI ...

product) to identify high-impact opportunities for AI-driven automation and intelligent tooling Stay at the forefront of agentic AI research — including LLM orchestration, RAG, function calling, and autonomous code generation — and bring those advances into our platform Mentor engineers across the team on AI-first development practices … with modern LLM orchestration tools, prompt engineering techniques, and AI/ML frameworks Experience with retrieval-augmented generation (RAG), function/tool calling, and evaluation-driven development for AI agents A builder's mentality — you don't just use AI tools, you create autonomous ...

develop, test and deploy LLM and agentic AI solutions Contribute to the development of LLM, Retrieval-Augmented Generation (RAG) and agentic AI solutions, including evaluation, optimisation and monitoring.Implement reliable and scalable AI solutions using established software engineering, MLOps and LLMOps practices.Contribute across … Proven experience engineering technology solutions in complex environments and supporting production operations Applied AI/ML and GenAI experience with knowledge of established patterns (RAG, tool use, guardrails, evaluation, agents) and an ability to evaluate tools and approaches Experience working with conversational AI platforms and customer-facing AI applications. Experience ...

data extraction from compensation statements, anomaly detection on payroll inputs, LLM-assisted user workflows, and retrieval-augmented generation (RAG) over tax and payroll guidance. Evaluate, integrate, and operationalize AI APIs, models, and toolchains within application architectures, ensuring responsible AI usage, cost management, and observability … reporting. Exposure to mobile ecosystems (iOS and Android) and API design supporting mobile clients for assignee/employee experiences. Experience with prompt engineering patterns, RAG architectures, vector databases, or AI orchestration frameworks (e.g., LangChain, Semantic Kernel, Azure AI Services). Familiarity with AI code generation and review workflows ...