176 to 200 of 842 Retrieval-Augmented Generation Jobs in the UK

AI. Experience developing AI-enhanced digital assistant solutions such as Microsoft Copilot. Practical experience with Retrieval-Augmented Generation (RAG) architectures and Machine Learning Operations (MLOps). Strong stakeholder engagement skills, with the ability to communicate technical solutions clearly to both technical and non-technical ...

Integrate AI/ML components into applications and operational workflows Design and implement Retrieval-Augmented Generation (RAG) solutions Evaluate LLM performance, identify failure modes, and implement mitigation strategies Test, debug, and improve non-deterministic AI systems Balance AI approaches with deterministic or statistical methods … performance Ability to debug complex, non-deterministic behaviours Strong communication skills to explain AI trade-offs and risks Bonus Skills Hands-on experience with RAG architectures and LLM tooling Experience working in regulated or high-assurance environments Familiarity with AI safety, risk, and governance considerations Background in software engineering (Python ...

from the ground up, with significant scope for ownership, innovation and career development. Key Responsibilities Design and deliver AI solutions using Microsoft Azure, including RAG, data classification, forecasting and anomaly detection. Identify opportunities to introduce AI into existing business processes and systems. Integrate AI solutions with Microsoft 365, SharePoint, Teams … take AI projects from prototype through to robust production deployment. Desirable Skills Experience with Retrieval-Augmented Generation (RAG). Knowledge of vector databases. Experience with AI frameworks such as Haystack, LlamaIndex or Semantic Kernel. Experience with forecasting, anomaly detection or data classification. Knowledge ...

electricity markets, battery optimisation and project revenues. Explore the use of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI copilots and autonomous agents to improve knowledge management and engineering productivity. Create scalable data pipelines that ingest, clean and integrate large datasets from weather ...

data systems. Strong understanding of AI-ready data architectures supporting analytics, machine learning, generative AI, Retrieval-Augmented Generation (RAG), vector databases, and knowledge graphs. Experience with sovereign data ecosystems and interoperability frameworks such as GAIA-X, IDSA, and DSIF, with the ability to innovate ...

coverageYour qualificationsEarly-career professional with proven commercial experience in: Troubleshooting Large Language Model (LLM) and Retrieval-Augmented Generation (RAG) applicationsRobust prompt and context engineeringData analysis (Excel, Anaplan or similar tools)Software development or quality assuranceLevel 2 or level 3 technical supportA degree in Mathematics ...

coverageYour qualificationsEarly-career professional with proven commercial experience in: Troubleshooting Large Language Model (LLM) and Retrieval-Augmented Generation (RAG) applicationsRobust prompt and context engineeringData analysis (Excel, Anaplan or similar tools)Software development or quality assuranceLevel 2 or level 3 technical supportA degree in Mathematics ...

unstructured data. Design and deliver LLM-powered applications: conversational AI, enterprise copilots, knowledge management, and workflow automation. Architect advanced retrieval using RAG, Agentic RAG, Graph RAG, knowledge-graph, and hybrid approaches. Design multi-agent systems with modern orchestration and reasoning architectures, including human-in-the-loop and autonomous … Expected Programming & engineering : expert Python; REST APIs and microservices; FastAPI; distributed systems; cloud-native architecture. LLM application delivery: prompt engineering, tool and function calling, RAG, and at least one production Agentic AI system. Cloud AI platform : deep experience with one of Azure, OpenAI, AWS Bedrock, Claude; Kubernetes and cloud-native ...

skills use, and memory systems and work hands-on with foundation models through fine-tuning, retrieval-augmented generation (RAG), and custom model integration. A partof your work will also involve engineering the AI context layer that makes these systems intelligent in practice connecting enterprise … faithfulness, translating findings into design improvements Architect and implement foundation model integrations selecting the right models, invocation patterns, and customization approaches (fine-tuning, RAG, custom integration) based on capability, cost, and performance trade-offs Design and build model adaptation and fine-tuning pipelines, applying working knowledge of transformer-based architectures ...

most cutting-edge defence and aerospace projects in the UK? If the prospect of developing software for projects such as a sixth-generation stealth fighter jet or a revolutionary Laser Directed Energy product excites you, then Leonardo would like to hear from you. Leonardo is seeking to recruit … fine-tuning large language models (LLMs). Experience building scalable pipelines, including APIs, vector databases, retrieval-augmented generation (RAG), and orchestration frameworks. Experience curating datasets, managing embeddings, and ensuring security, privacy, and responsible AI practices. Experience in prompt engineering, with the ability to design ...

most cutting-edge defence and aerospace projects in the UK? If the prospect of developing software for projects such as a sixth-generation stealth fighter jet or a revolutionary Laser Directed Energy product excites you, then Leonardo would like to hear from you. Leonardo is seeking to recruit … fine-tuning large language models (LLMs). Experience building scalable pipelines, including APIs, vector databases, retrieval-augmented generation (RAG), and orchestration frameworks. Experience curating datasets, managing embeddings, and ensuring security, privacy, and responsible AI practices. Experience in prompt engineering, with the ability to design ...

Discovery Optimisation Continuous optimisation of our job search experience, leveraging advanced retrieval and ranking algorithms. Research, implement, and experiment with next-generation search techniques to enhance relevance and accuracy for users globally. Collaborate with engineering teams to integrate data science models seamlessly into our tech stack. … require sponsorship. Nice to have: Experience of agentic frameworks Experience with advanced search techniques, specifically Retrieval-Augmented Generation (RAG) and vector search. Prior experience working within the online classified advertising or job board industry. An active personal website or Github account with examples ...

that means leading the team(s) across surfaces like: Diagnosis & needs assessment — AI-heavy services (retrieval-augmented generation (RAG), LLM-scored assessment) that turn raw signal into a picture of where a learner or employer actually is. Prescription & eligibility — build the product which helps … out. Stack & how we leadTypeScript core (React/Next.js, Node) with PostgreSQL and RabbitMQ as the event backbone, plus Python and Elixir services — from RAG pipelines to a Claude-powered edge-native product. GitHub, CircleCI, Datadog. AI-assisted development is first-class, not bolted on. You'll lead full-stack ...

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 ...

quality outcomes. Experience in one or more of the following would be beneficial: Semantic Kernel Retrieval-Augmented Generation (RAG) architectures Microsoft Fabric Docker Cloud-native services Managed services platforms Centerprise is a well-established UK technology provider with over 40 years of experience delivering ...

APIs and backend services that power enterprise customer integrations Owning the LLM application layer, including retrieval-augmented generation (RAG) workflows Improving model performance, reliability, evaluation frameworks, monitoring, and cost optimisation Working across the stack to deliver customer-facing features and platform capabilities Collaborating with … engineering expertise, ideally within API-first products Experience with Node.js and TypeScript, or a proven ability to transition successfully between technology stacks Understanding of RAG architectures, evaluation frameworks, guardrails, monitoring, and model optimisation Experience managing token usage, infrastructure costs, and scalability challenges in AI products Comfortable working autonomously ...

Apply clean code, automated testing, CI/CD, observability and other modern engineering principles Build and integrate AI-enabled features, including LLM-powered services, RAG and agent-based workflows where appropriate Use AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor or similar to improve engineering productivity Develop … Desirable: Experience integrating AI into production systems (e.g. chat interfaces, automation, intelligent search) Familiarity with Retrieval-Augmented Generation (RAG), vector databases, or embeddings Experience with cloud platforms (AWS preferred) Awareness of emerging AI tooling (e.g. MCP, A2A, Threads or similar) Open-source contributions ...

platforms. Hands-on experience with AI orchestration and agent frameworks including LangChain, LangGraph, Semantic Kernel, LlamaIndex, CrewAI, and AutoGen. Strong knowledge of Prompt Engineering, RAG, Vector Databases (Pinecone, Weaviate, Chroma, FAISS, Azure AI Search), Model Fine-Tuning, LLMOps, and Secure AI practices. Enterprise Architecture & Security Proficiency in enterprise architecture frameworks ...

build scalable agentic AI platforms that integrate Large Language Models (LLMs), multi-agent orchestration and retrieval-augmented generation (RAG) patterns into production-ready enterprise solutions. You will focus on creating reusable platform components, orchestration engines and governance frameworks that allow complex AI workflows ...

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 ...

development and deployment of cutting-edge Gen AI models and solutions. You will be responsible for building, testing, and maintaining our Gen AI, RAG and NLP solutionsYou will work throughout the whole life cycle of data science projects: design, implementation, production and beyond. You will deliver efficient and production-ready … science pipelines (such as pre-processing and model inference) and their deployment together with software engineering teamOptimizing and customizing Retrieval Augmented Generation (RAG) pipelines to meet specific project requirements that involve content ingestion, machine translation, and contextualized information retrievalIngesting, preprocessing, and transforming large-scale ...

automation and optimisation. Design and build AI solutions using technologies such as LLMs, agents and retrieval-augmented generation (RAG). Create practical roadmaps for AI adoption, including prioritised implementation plans. Engage with business stakeholders to communicate opportunities, risks and recommendations. Develop, deploy and scale … delivering end-to-end AI solutions in commercial environments. Capability to work across strategy, architecture and hands-on engineering. Expertise with LLMs, AI agents, RAG frameworks and modern AI tooling. Experience assessing business processes and translating requirements into technical solutions. Strong stakeholder management and communication skills. Background working within smaller ...

multi‐modal large language models across text, image, audio, and video Design and implement agentic workflows using prompt engineering, Retrieval‐Augmented Generation (RAG), APIs, and enterprise data integrations Fine‐tune, optimize, and deploy large language and multi‐modal models with a focus on scalability … within agile delivery environments Bonus Points For Experience building AI agent frameworks or autonomous orchestration platforms Knowledge of vector databases, semantic search, and advanced RAG architectures Experience with cloud platforms such as AWS, Azure, or GCP for AI workloads Familiarity with financial services, banking, or regulated enterprise environments Exposure ...

Agentic AI Multi-agent systems Tool calling Function orchestration Workflow automation Planning and reasoning patterns Human-in-the-loop design Knowledge & Retrieval RAG architectures Vector databases Semantic search Enterprise search Document ingestion Knowledge graphs (advantageous) Integration APIs Event-driven architectures Microsoft ecosystem ServiceNow CRM/ERP integration Identity ...

Azure AI Experience building Agentic AI workflows, orchestration frameworks, AI copilots, or autonomous process automation solutions Knowledge of AI-driven APIs, semantic search, RAG architectures, and vector database integrations Azure certifications such as AZ-900, AZ-204, or AI-900 would be advantageous Key Responsibilities Design, develop, and maintain scalable ...