26 to 36 of 36 Retrieval-Augmented Generation Jobs in the North of England

Forward Deployed Engineer Generative AI/LLM Deployment GenAI | LangChain | RAG | AWS | Kubernetes | Customer-Facing We are hiring a Forward Deployed Engineer to lead the deployment of production-grade Generative AI and LLM solutions into enterprise environments. This is a hands-on, customer-facing role focused on building and deploying … RAG pipelines, multi-agent systems and fine-tuned LLM applications using tools such as LangChain and LangGraph. You will embed with client teams, own technical delivery from prototype to production, and demonstrate measurable KPI impact. Key Responsibilities Design and deploy GenAI/LLM applications (RAG, agentic AI, fine-tuning) Lead ...

Foundry environment. This is a hands-on role focused on building scalable, production-ready AI systems using LLMs, RAG (retrieval augmented generation), vector databases, embeddings and Azure AI services. Key Responsibilities Design and develop LLM-powered applications, AI agents and Copilot solutions Build … optimise RAG pipelines, embeddings and vector search Integrate AI solutions with enterprise systems, APIs and cloud platforms (Azure) Implement secure-by-design AI engineering, monitoring and observability Develop reusable components including prompt libraries, agent frameworks and connectors Prototype, test and improve model performance, reliability and scalability Key Skills Strong experience ...

/B experiments and performance dashboards. • Integrate AI agent functionality with applications through MCP servers and reliable tool configurations. • Develop secure and scalable RAG pipelines, including ingestion, text processing, metadata handling and vector search in GCP. • Embed security, compliance, GDPR controls and best‐practice engineering with clear documentation and stakeholder … Strong Python skills for backend services, SDKs, API development, authentication and testing. • Hands‐on experience working with LLMs, embeddings, prompt engineering, tool calling and RAG design. • Practical knowledge of GCP services including Vertex AI, Model Garden, BigQuery, Cloud Run and Google’s ADK. • Experience with document and data processing using ...

Applied AI Software Engineer - LangChain, LangGraph, RAG, Knowledge Graphs A high-growth, technology-led scale-up (backed by a global leading organisation) is expanding its engineering capability following a highly successful 2025. As part of significant continued investment, they are hiring a Software Engineer to lead the design and development … next-generation AI products and services across Finance, supporting both internal operations and external platforms. This is an opportunity to work in a modern, cloud-native engineering environment, building intelligent agentic AI systems that can reason, plan and act autonomously. You will take ownership of solutions ...

influence technical strategy, architecture, and best-practice from day one. THE ROLE: Build and operate production-ready AI agents on GCP Design robust RAG pipelines covering ingestion, text processing, vector search and secure data handling. Implement evaluation frameworks, monitoring, A/B testing and performance dashboards for latency, cost … Engineering or Software Engineering with applied AI delivery. Deep hands-on expertise with GCP services Strong Python skills Practical experience with LLMs, embeddings, RAG architectures and vector databases. A track record of building production-grade AI systems, including observability, evaluation and automated testing. DevOps capability across CI/CD, Docker ...

enterprise-grade AI capabilities. What Youll Be Doing Designing and building Copilot solutions, intelligent agents, and LLM workflows Developing scalable AI components including RAG pipelines, embeddings, and vector search Integrating AI solutions into enterprise systems, APIs, and cloud platforms Conducting rapid prototyping to validate use cases, UX, and model performance … Essential Skills for the AI product developer Proven experience building solutions using LLMs, AI APIs, and Copilot Studio or similar tools Strong understanding of RAG architectures, vector databases, and embeddings Experience with Azure AI and cloud-native development Solid knowledge of secure engineering practices including authentication, data protection, and auditability ...

internal operations and develop new intelligent products. Their AI capability is expanding quickly, creating strong opportunities for growth. The Role * Build AI solutions across RAG, agentic workflows, and LLM applications.* Develop automation tools, chatbots, and content generation systems.* Work with AWS, LangChain, and vector databases.* Contribute to both … internal and future client-facing products. Your Skills and Experience * Strong commercial experience with RAG, agents, and LLM tooling.* Confident with Python, AWS, and LangChain or similar frameworks.* Hands on with vector databases and retrieval pipelines.* Comfortable identifying problems and delivering end-to-end solutions ...

attention to detail. Ability to work effectively within Agile squads and cross-functional environments. Desirable: Exposure to AI testing methods (e.g., validating LLM outputs, RAG consistency, AI behaviour evaluation). Experience using AI-powered QA tools or test-generation frameworks. Knowledge of cloud environments (AWS/Azure ...

Location Manchester, UK (Hybrid - 3 days per week in office) About ServisBOT ServisBOT is building the next generation of AI-driven enterprise automation for regulated industries — a secure, compliant SaaS platform where AI and humans work together to deliver outcomes our clients can trust. We partner with global … implementation in client environments and ensuring we deliver measurable value. You’ll also build confidence in key AI concepts like prompt engineering, LLMs, and RAG, helping translate customer needs into practical, trustworthy AI-enabled solutions. Key Responsibilities Problem Definition & Discovery (Supported Ownership) Support discovery activities for product initiatives and customer ...

business. Key responsibilities include: • Designing and delivering an AI platform that supports large‐scale agentic automation and end‐to‐end claims journeys • Building robust RAG pipelines, LLM‐based systems, and deployment frameworks • Developing AI agents for claims handling, internal tooling, and customer‐facing chat solutions • Evolving an internal AI assistant … engineering or software engineering with a focus on LLMs and production AI systems • Expertise in deploying AI models and agents at scale, including RAG, embeddings, and LLM tooling • Hands‐on cloud engineering experience, ideally in GCP and its AI ecosystem • Strong Python engineering ability and experience building production‐grade services ...

break into AI properly, not just talk about it? I'm working with a team building real world AI applications using LLMs and RAG and they're open to junior to mid-level developers who've already started exploring this space (even through personal projects). What … doing: Building full stack apps (React/Next.js or Node/NestJS) Working with LLMs (OpenAI, Claude etc.) Developing RAG-based features (smart search, AI-driven tools) Integrating AI into real products used by customers What they're looking for: Solid JavaScript/TypeScript experience Some hands on work with ...