1 to 25 of 113 Permanent Retrieval-Augmented Generation Jobs in England

organization. The team designs, develops, and supports enterprise-grade AI applications, including Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI solutions. Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those … success criteria for AI initiatives. Design, develop, and deliver scalable AI solutions, including Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, and intelligent automation capabilities aligned to business objectives. Evaluate technology, model, and platform options, providing recommendations based on business value, cost, risk, strategic ...

features and applications using LLMs, including intelligent document processing, information extraction and automated workflows. Develop retrieval-augmented generation (RAG) solutions that connect LLMs with internal data, documents and other knowledge sources. Build and integrate APIs to connect applications, databases, CRM platforms and third-party … LLMs: Practical experience integrating large language models into applications or developing AI-powered functionality. Retrieval-Augmented Generation (RAG): Experience building or implementing RAG pipelines that enable LLMs to retrieve and use relevant information from documents, databases or other knowledge sources. Application architecture: An understanding ...

enterprise standards. Design enterprise-scale AI architectures covering agent orchestration, large language models (LLMs), retrieval-augmented generation (RAG), knowledge management, integrations, governance, security, and observability. Assess client technology landscapes, data estates, cloud platforms, and security frameworks to establish the foundations required for successful … focused organizations. Technical Knowledge Strong understanding of Large Language Models (LLMs), Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), AI orchestration frameworks, and AI application architectures. Knowledge of cloud platforms including Microsoft Azure, AWS, and Google Cloud. Experience with modern data platforms including Databricks ...

conversational assistants, workflow automation and intelligent document processing Developing applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and agent-based approaches Taking solutions from prototype through to deployment, monitoring and continuous improvement Building and maintaining APIs, integrations and data pipelines that support … Demonstrable ability to learn new technologies quickly Desirable Experience Agentic AI or AI agent frameworks Retrieval-Augmented Generation (RAG) Workflow automation platforms AI evaluation, monitoring or observability Experience working within regulated environments Agile delivery experience About YouThis organisation is placing particular emphasis on mindset ...

agentic AI. Continuous Learning: Stay updated with the latest trends in the AI engineering field, such as the modern AI stack, synthetic data generation, and Explainable AI. … Skills/Experience: Engineering Foundations: Strong proficiency in Python and robust software engineering principles, with experience operating as part of engineering teams. Generative AI & RAG: Proven experience working with LLMs and designing Retrieval-Augmented Generation (RAG) architectures, including knowledge of semantic search and vector ...

PyTorch FastAPI Knowledge Graphs Kubernetes Docker Infrastructure as Code MLOps Event-Driven Architecture Vector Databases Retrieval-Augmented Generation (RAG) Technology Stack Python SQL FastAPI PyTorch Docker Kubernetes AWS Azure Git CI/CD Knowledge Graphs AI/Large Language Models (LLMs) Amazon Bedrock Azure ...

standards across AI projects. Design and deliver solutions involving generative AI, large language models (LLMs), retrieval-augmented generation (RAG), prompt engineering and agentic AI. Establish robust approaches to model evaluation, monitoring, performance measurement and continuous improvement. Drive high-quality engineering practices, including Python development … machine learning solutions into production. Strong technical leadership and architecture experience across AI engineering and software delivery. Practical knowledge of generative AI, LLMs, RAG, prompt engineering, agentic AI and model evaluation. Strong Python development skills and a sound understanding of software engineering best practice. Experience delivering AI solutions at scale ...

Collaborate with multidisciplinary teams to develop Generative AI proof-of-concepts using technologies such as Retrieval-Augmented Generation (RAG) and intelligent agents. Scale successful proof-of-concepts into robust, production-ready solutions. Design and develop full stack applications across both AI-driven and traditional … success. You will work on impactful projects, contribute to the adoption of emerging technologies and play a key role in delivering next-generation AI solutions. Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built ...

Agents & Automation Design, develop, and manage AI agents, copilots, and workflow automation solutions. Build Retrieval-Augmented Generation (RAG) applications leveraging internal business data. Develop intelligent assistants supporting operational, engineering, customer service, and business functions. Implement multi-agent workflows and orchestration frameworks. Monitor and optimise … enterprise environments. Strong Python development skills. Experience integrating and consuming REST APIs. Hands-on experience with Docker and Kubernetes. Knowledge of vector databases, embeddings, RAG architectures, and LLM orchestration frameworks. Experience with cloud technologies, networking, identity and access management, and security controls. Experience integrating AI solutions with Microsoft 365 technologies ...

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 ...

Platform Engineer LLMs | RAG | Python | Cloud Infrastructure Manchester City Centre - 5 days a week onsite Up to £100,000 DOE The Opportunity We're looking for an AI Platform Engineer to build, optimise and maintain the infrastructure behind a growing portfolio of AI-powered applications. You'll focus on developing … scalable, reliable services supporting large language models (LLMs), retrieval-augmented generation (RAG), intelligent search and conversational AI. You'll take ownership of existing solutions while helping bring new AI capabilities into production. Key Responsibilities - Design, build and optimise production-grade AI platforms, RAG pipelines ...

help onboard new team members. Work alongside senior engineers, including colleagues experienced in AI and retrieval-augmented generation (RAG), to build the teams confidence in applying AI to practical problems. Contribute to frontend and backend work according to your experience, developing a broader understanding … problems customers face and how users interact with our products. Explore relevant approaches with senior engineers, drawing on any experience of vector search, embeddings, RAG, fine-tuning, prompt engineering or AI orchestration frameworks such as LangChain. Help evaluate model output quality through structured examples and lightweight evaluation sets. Where relevant ...

agent-based patterns, workflow orchestration and enterprise AI integration. Practical experience applying techniques such as retrieval-augmented generation (RAG), knowledge grounding, prompt engineering and human-in-the-loop design patterns. Experience designing secure and controlled AI solutions, including guardrails, responsible AI, explainability and governance ...

industry is a plus. Strong foundational understanding of modern AI and agentic application patterns, including retrieval-augmented generation (RAG), semantic search, and agent-based system design. Hands-on experience building backend services, APIs, and production systems. Experience working across architecture, data, and platform concerns ...

shipping AI-powered products end-to-end using LLM technologies. Owning and scaling the retrieval-augmented generation (RAG) and AI application layer. Developing secure, production-grade systems including guardrails, evaluation frameworks, monitoring, caching, and token cost optimisation. Working across the stack, including backend services ...

. Experience building pipelines for structured and unstructured data using both vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise AI solutions. Experience leading technical discovery sessions. Preferred qualifications: Masters degree or PhD in Artificial Intelligence, Computer Science, or a related ...

Data, AI & Intelligent Systems Expertise: Experience or strong interest in one or more of the following: Generative AI, LLMs, Retrieval Augmented Generation (RAG) and AI applications Agentic AI, AI agents, intelligent assistants and AI-enabled automation Prompt engineering, AI evaluation and Responsible ...

GitHub Actions, Azure DevOps, RBAC and Cost Controls. Software Engineering: Clean Code (SOLID, DRY), DDD, modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens. Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK. ...

experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems Experience designing and scaling low-latency, customer-facing ...

Experience across several of the following areas would be advantageous: * Agentic AI * AI Agents & Autonomous Workflows * Generative AI & LLMs * Retrieval Augmented Generation (RAG) * Multi-Agent Systems * MLOps/LLMOps * LangGraph, LangChain, Semantic Kernel, CrewAI or AutoGen * OpenAI Agents, Microsoft Copilot Studio and MCP * Azure … Agents, Generative AI, LLMs, Machine Learning, Data Science, Platform Engineering, LangGraph, LangChain, Semantic Kernel, CrewAI, OpenAI Agents, Microsoft Copilot Studio, MCP, MLOps, RAG, SaaS, Cambridge. ...

organisations from identifying opportunities through to enterprise adoption and measurable business impact. Strong understanding of Generative AI, Agentic AI, Retrieval Augmented Generation (RAG), intelligent assistants and AI-enabled automation, with awareness of major enterprise AI ecosystems such as OpenAI, Google, Anthropic and Microsoft. Experience … Strategy Director, Enterprise AI Consultant, AI Consulting Lead, Data & AI Strategy Consultant, Generative AI, GenAI, Agentic AI, AI Agents, RAG, Retrieval Augmented Generation, Decision Intelligence, Intelligent Automation, AI Operating Models, AI Architecture, Data Platforms, Semantic Layers, Data Products, Responsible AI, AI Governance, Cloud Data ...

solutions. You will help clients translate business challenges into scalable AI architectures, leveraging Agentic AI, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and modern cloud technologies. The places that you work from day to day will vary according to your role, your needs … home 100% of the time. Your Role Design and develop enterprise AI solutions, with a particular focus on Agentic AI, Generative AI, and RAG architectures. Work with clients to understand business requirements and translate them into scalable technical solution designs. Build, integrate, and optimize AI applications using Python and leading ...

ability to influence without line authority, including winning over sceptics Helpful: Bitbucket, Jenkins/Harness, Docker, Kubernetes, AWS, FastAPI, MCP, DORA-style measurement, RAG and vector search, self-hosted open-weight models, or a regulated environment such as gambling or financial services Guidant, Carbon60, Lorien & SRG - The Vertage Group Portfolio ...

track record delivering enterprise-scale AI/ML solutions into production Strong experience leading technical teams and complex transformation programmes Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands-on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms ...

Actions, Azure DevOps, RBAC and cost controls. Solid software engineering fundamentals: Clean Code (SOLID, DRY), DDD, modular architecture, TDD and code quality tooling. Desirable: RAG pipelines, MCP, LLM integration (OpenAI, Gemini, Hugging Face models), LangSmith, TruLens, and agentic frameworks such as LangChain, CrewAI, Autogen, OpenAI Agents and Google ADK. … React Developer, Next.js Developer, TypeScript Developer, Azure OpenAI, Vertex AI, LangChain, LangGraph, CrewAI, Autogen, OpenAI Agents SDK, Google ADK, RAG, retrieval augmented generation, MCP, LangSmith, TruLens, prompt engineering, Docker, Kubernetes, AKS, GCP, Azure DevOps, GitHub Actions, PostgreSQL, BigQuery, TDD, DDD. Deerfoot Recruitment Solutions ...