201 to 225 of 963 Retrieval-Augmented Generation Jobs in England

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

iterate on AI systems in production environments, including performance tuning and cost optimization.Design and build Retrieval-Augmented Generation (RAG) systems using embeddings, vector databases, and semantic search.Build and optimize prompts and interaction strategies for LLMs to achieve desired outcomes in agentic systems.Integrate various tools … tool usage, and multi-agent systems.Familiarity with AI workflow orchestration and agentic frameworks (e.g., LangChain, LangGraph, Crew AI, Haystack, or similar).Practical experience with RAG architectures, embeddings, vector databases, and semantic search.Experience working with Model Context Protocol (MCP) Servers.Experience with RESTful APIs and integrating external services.Solid understanding of software development ...

systems in production environments, including performance tuning and cost optimization. Design and build Retrieval-Augmented Generation (RAG) systems using embeddings, vector databases, and semantic search. Build and optimize prompts and interaction strategies for LLMs to achieve desired outcomes in agentic systems. Integrate various tools … multi-agent systems. Familiarity with AI workflow orchestration and agentic frameworks (e.g., LangChain, LangGraph, Crew AI, Haystack, or similar). Practical experience with RAG architectures, embeddings, vector databases, and semantic search. Experience working with Model Context Protocol (MCP) Servers. Experience with RESTful APIs and integrating external services. Solid understanding ...

whether proposed outcomes can be achieved. You will work across customer-facing AI use cases including personalisation, customer decisioning, customer service agents, retrieval-augmented generation solutions and agentic workflows.This is a senior role, but it remains technical. You will need to review architectures, challenge … enough to guide delivery teams and ensure solutions are ready for production.What You Will DoReview and challenge solution architectures, covering model selection, retrieval-augmented generation, agentic workflows, evaluation frameworks, guardrails, scalability and cost.Identify technical and delivery risks early, including data quality issues, integration complexity ...

whether proposed outcomes can be achieved. You will work across customer-facing AI use cases including personalisation, customer decisioning, customer service agents, retrieval-augmented generation solutions and agentic workflows. This is a senior role, but it remains technical. You will need to review architectures … guide delivery teams and ensure solutions are ready for production. What You Will DoReview and challenge solution architectures, covering model selection, retrieval-augmented generation, agentic workflows, evaluation frameworks, guardrails, scalability and cost. Identify technical and delivery risks early, including data quality issues, integration complexity ...

world impact. This position sits within a growing AI function and will focus heavily on Retrieval-Augmented Generation (RAG), agentic workflows, evaluation frameworks, and LLM optimisation. Key Responsibilities: Design and develop scalable RAG pipelines and generative AI workflows Build solutions using LangChain, LangGraph … contribute to technical best practices Key Requirements: Strong Python engineering experience Commercial experience building production-grade AI/ML systems Hands-on experience with RAG architectures and LLM workflows Experience with LangChain, LangGraph, and/or Llama Index Understanding of evaluation methodologies for generative AI Experience working within scalable cloud ...

Build and integrate AI-powered features into web applications and enterprise tools. Build and optimize Retrieval-Augmented Generation (RAG) solutions to power chatbot interactions Work both independently and paired with other team members to ensure efficient delivery of prioritised features. Take part … Experience using modern AI-assisted and agentic development workflows in day-to-day engineering usingAI/ML APIs and SDKs Hands-on experience developing RAG solutions or working with LLMs for chatbots is preferred In-depth understanding of CI/CD and the tools used to implement them, such ...

wider 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 FullStack applications for both GenAI and non-GenAI projects. Support ...

/functions callable by AI agents (tool schemas, function calling, structured outputs). Experience with retrieval-augmented generation (RAG) : vector databases (e.g., Pinecone, Weaviate, pgvector), embeddings, and chunking strategies. Working knowledge of prompt engineering and evaluation techniques for agent reliability, safety, and cost control. ...

agentic architectures. Good understanding of modern AI concepts and practices, including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Prompt Engineering AI Guardrails AI Evaluation Frameworks Experience with AI frameworks such as Agent Development Kit (ADK), LangChain, LangGraph, CrewAI, or similar. Experience working with ...

transfer learning, text and token classification. Working knowledge of large language models, including prompting and retrieval-augmented generation (RAG).Experience or coursework in Deep Learning frameworks like PyTorch or TensorFlow.Strong problem-solving skills and a curiosity for learning new technologies.Good verbal and written communication ...

cross-functional organizations.Deep knowledge of modern AI technologies including large language models (LLMs), agentic frameworks, retrieval-augmented generation (RAG), vector databases, and automation platforms — with the credibility to evaluate vendor claims and guide architectural decisions.Experience owning AI governance: building acceptable use policies, risk tiering ...

both customers and organisations. Modern AI architecture expertise. Deep understanding of machine learning, LLMs, retrieval-augmented generation (RAG), agentic systems and the architectural patterns used to deploy AI solutions at enterprise scale. Engineering and cloud foundations. Strong understanding of software engineering, data architecture ...

both customers and organisations. Modern AI architecture expertise. Deep understanding of machine learning, LLMs, retrieval-augmented generation (RAG), agentic systems and the architectural patterns used to deploy AI solutions at enterprise scale. Engineering and cloud foundations. Strong understanding of software engineering, data architecture ...

value for both customers and organisations.Modern AI architecture expertise. Deep understanding of machine learning, LLMs, retrieval-augmented generation (RAG), agentic systems and the architectural patterns used to deploy AI solutions at enterprise scale.Engineering and cloud foundations. Strong understanding of software engineering, data architecture ...

value for both customers and organisations.Modern AI architecture expertise. Deep understanding of machine learning, LLMs, retrieval-augmented generation (RAG), agentic systems and the architectural patterns used to deploy AI solutions at enterprise scale.Engineering and cloud foundations. Strong understanding of software engineering, data architecture ...

will combine deep software engineering experience, excellent judgment and a demonstrable interest in AI to help shape the way we build our next generation of products. Initially working in a small, focused team, you will help lead and progress the development of our foundational AI-native/… principles (REST, SPA...). Microservice architecture, AWS and DevOps. Building LLM-powered features: tool-calling, retrieval-augmented generation (RAG), evaluation/eval harnesses and observability (desirable). Familiarity with model-agnostic tooling and routing, e.g. a proxy/gateway layer (desirable). Agile manifesto ...

generative AI solutions for scientific and knowledge-discovery applications.Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question answering, and evidence-grounded insight generation.Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks … practices.Strong Python skills and solid machine learning fundamentals.Experience working with large-scale text or content-rich datasets and modern AI/ML frameworks.Experience with RAG, semantic, vector, or hybrid search, along with experimentation and evaluation approaches that measure user impact.Familiarity with cloud platforms and modern software engineering practices.Strong communication, collaboration ...

generative AI solutions for scientific and knowledge-discovery applications. Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question answering, and evidence-grounded insight generation. Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks … skills and solid machine learning fundamentals. Experience working with large-scale text or content-rich datasets and modern AI/ML frameworks. Experience with RAG, semantic, vector, or hybrid search, along with experimentation and evaluation approaches that measure user impact. Familiarity with cloud platforms and modern software engineering practices. Strong ...

reference architectures, POV frameworks, or architectural playbooks — at scale.Fluency across the modern data and AI stack: cloud data platforms (Snowflake, Databricks, BigQuery), agentic frameworks, RAG, vector databases, LLM orchestration, data governance, and enterprise integration patterns.Experience with prompt engineering, agent lifecycle management, and hands-on prototype development.Hands-on proficiency in programming … Redshift.AI & Agentic Architecture Foundational ML concepts, data preparation, Python, applied AI, Generative AI, prompt engineering, retrieval-augmented generation (RAG), vector stores, and agentic architectures. Hands-on familiarity with platforms like Databricks, Snowflake, SageMaker, or Vertex. Agent lifecycle management, observability, and governance frameworks.Agentforce & Salesforce Platform ...

help build the data foundations that power enterprise search, knowledge discovery, AI applications and Retrieval-Augmented Generation (RAG). What you'll be doing Design and build scalable ETL/ELT data pipelines across multiple enterprise data sources Develop data solutions using BigQuery, Google ...

systems, or conversational AI.Ideally, you also have experience with large language models (LLMs), foundation models, retrieval-augmented generation (RAG), fine-tuning, prompt engineering, or agentic AI architectures. Hands-on experience with AWS AI/ML services such as Amazon Bedrock, Amazon SageMaker, Amazon ...

LLMs and agentic AI. Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG) and orchestration of agentic AI systems. Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data, and integrating non-traditional data sources. ...