126 to 150 of 172 Retrieval-Augmented Generation Jobs in the UK excluding London

pipelines. The engineer must also ensure solution quality through evaluation frameworks, ground-truth validation, and defined performance metrics. Key Responsibilities Design and buildGenAI/RAG-based applicationsusing data from multiple enterprise systems. Integrate withstructured and unstructured data sources, including databases, APIs, files, and document repositories. Develop pipelines toparse and extract ...

Engineer | £80,000 - £110,000 | London/Hybrid | Python | LLM | GenAI | RAG | AI Agents | Looking to join one of the fastest growing AI companies in Europe Want to have autonomy and own end-to-end solutions I am currently supporting a brilliant AI company who are looking ...

Skills Strong banking domain expertise (retail, lending, payments, contact center) Expertise in Conversational AI/IVR and GCP architecture Knowledge of Agentic AI, RAG, and API-led integrations Exceptional stakeholder engagement and influencing skills Experience 1218+ years in enterprise architecture/solution design Proven experience in onsite client-facing roles ...

with cloud‐native application architectures (containers, microservices, serverless) and the security considerations for these environments. Familiarity with AI‐integrated application risk, including LLM integration, RAG architectures and AI‐assisted development tooling. Strong written and verbal communication skills, able to translate technical risk into business language and vice versa. Benefits ...

grade deployment. The role: - Design AI and GenAI architecture strategies and roadmaps - Build scalable AI/ML and Agentic AI platforms - Work across LLMs, RAG, embeddings and semantic search - Support AI deployment, governance and integration patterns - Collaborate with engineering, data, DevOps and business teams - Advise clients on AI platform capability … implementation strategy Tech environment: Python LLMs (prompt engineering, fine-tuning, RAG) LangChain/LangGraph Agent frameworks Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructure What you'll bring: - Experience designing enterprise AI or ML architectures - Strong grasp of cloud and modern data platforms ...

Robotics team following continued growth and investment. This is an exciting opportunity to join a multidisciplinary engineering team developing next-generation intelligent systems that combine AI, machine learning and robotics to solve complex real-world challenges. Working closely with software engineers, data scientists and product teams … modern software architecture. Experience working within Agile development environments. Excellent communication and stakeholder engagement skills. Desirable Experience with ROS/ROS2. Experience with LLMs, RAG or Agentic AI architectures. Knowledge of reinforcement learning or motion planning. Familiarity with Docker, Kubernetes and CI/CD. MSc or PhD in Computer Science ...

scalable, reliable data products and AI services. The successful candidate will bring technical experience across generative AI, large language models, retrieval augmented generation, machine learning, computer vision, geospatial data science and MLOps. They will work with multidisciplinary teams to identify valuable use cases, shape … modern machine learning frameworks such as PyTorch, TensorFlow or Keras. Practical experience with generative AI, large language models, embedding models, retrieval augmented generation, AI agents, model evaluation and fine‐tuning techniques. Experience designing and operating end‐to‐end MLOps workflows, including model training, deployment ...

highly regulated environments Strong understanding of software architecture and API design IT WOULD BE NICE FOR THE AI SOFTWARE ENGINEER TO HAVE.... Experience with RAG pipelines and vector databases Knowledge of MLOps tooling and CI/CD pipelines Exposure to Palantir Foundry or similar data platforms Experience working on National … Engineer/Machine Learning Engineer/LLM Engineer/Python/AWS/Azure/Docker/Kubernetes/Generative AI/NLP/RAG/MLOps/UKSV DV/Outside IR35/London ...

Language Models (LLMs), AI-assisted development tools, and modern AI frameworks. Has understanding of AI system architecture, prompt engineering, vector databases, RAG (Retrieval-Augmented Generation), and AI service integration and has experience evaluating Has knowledge of database systems and excellent problem-solving skills ...

tooling and standards while leading hands-on development and mentoring engineers across cloud and API-enabled platforms. You will work with Python, LLMs, and RAG, influencing technical direction and delivering scalable AI capabilities within the organization. #J-18808-Ljbffr ...

powered capabilities, and own end‐to‐end delivery across global teams, ensuring secure, scalable, and compliant implementations. The role requires deep expertise in LLMs, RAG, PyTorch/TensorFlow, and building high‐performance AI APIs. Hybrid work with competitive benefits is offered. #J-18808-Ljbffr ...

learning is essential, with solid NLP and financial knowledge and hands‐on implementation experience. The role focuses on advanced techniques such as semantic search, RAG, NER, prompt engineering, and personalization for content #J-18808-Ljbffr ...

will own delivery, scale the function, and define its future. You\'ll work with Claude, Claude Code, MCP, LangChain to implement multi-agent systems, RAG pipelines, and tooling. This is a hands-on leadership role with three engineers initially. The role is fully remote within UTC -1 to UTC +3 ...

Technology, Media or Telecoms sectors. Deep understanding of the Generative AI landscape and its commercial applications, with familiarity across technologies such as LLMs, RAG architectures, vector search, prompt design and AI platform operations. Experience overseeing the end-to-end delivery of AI initiatives, working closely with technical specialists to shape ...

improve Design and ship multi-agent systems and production-grade automations that measurably improve how internal teams and customer-facing staff work Build RAG pipelines for internal knowledge retrieval that ground agents in real organisational context Keep the AI tooling stack healthy as usage scales across 2,500+ … development Hands-on experience building multi-agent systems using agentic frameworks — LangChain, LangGraph, MCP, Google ADK or similar Experience with RAG pipelines — retrieval-augmented generation for internal knowledge and workflow automation Background in enterprise tooling — rapid prototyping tools (Vercel/Railway), identity automation (Entra ...

solutions and can clearly explain both the concepts and the implementation behind them. Essential Experience Building and deploying production LLM applications Strong experience with RAG including: Document ingestion Chunking strategies Embeddings Vector search and retrieval Context engineering Prompt orchestration LLM deployment experience, not just experimentation Azure OpenAI, Ollama … Hallucination detection Response quality measurement Accuracy testing Prompt and context engineering What We're Looking For You should be able to confidently explain: What RAG is and how to build it end to end How embeddings and vector databases work How to deploy and operate LLMs in production ...

CloudWatch, Splunk, Docker/ECS). Optimize application performance and reliability. Build and integrate AI-driven features (LLMs, intelligent APIs, automation workflows). Implement RAG patterns, AI pipelines, and model integrations (Bedrock, SageMaker). Optimize and monitor models for accuracy, drift, bias, and observability. Leverage Claude/equivalent frontier models … back end app dev side Front end experience a plus but not necessarily needed Python/typescript for coding Understand AI capabilities, handle RAG patterns Benefits at IntelliBee Long-Term Stability: Join us on a multi-year opportunities with room to grow. Comprehensive Health Coverage: Access quality healthcare benefits ...

Requirements gathering from business users AI & Automation Experience with Generative AI tools Prompt engineering Basic understanding of LLMs and RAG (Retrieval Augmented Generation) AI use case identification, assessment and delivering from concept through to implementation and adoption. Familiarity with Microsoft Copilot, ChatGPT Enterprise ...

Forward Deployed Engineer programme. Key Responsibilities Architect and govern production‐grade agentic systems at enterprise scale: multi‐agent orchestration across complex environments, RAG pipelines, policy‐based routing, memory management, and programme‐level lifecycle observability Define RAG pipeline standards across engagements: establish chunking and embedding strategies, set quality benchmarks, and ensure … depth, not tutorial level Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOps fundamentals: eval harness design, prompt versioning, and production observability Cloud‐native engineering maturity: Kubernetes ...

Manchester Hours Full time Working Pattern Hybrid, 40% (or two days) in our Manchester office. What you'll be doing Develop the next generation of autonomous AI for colleagues and customers, focusing on safety, security and scalability. Lead multiple engineering teams to design, build and run AI agents … enabling teams to deliver at pace. Hands‐on experience with agentic AI: building LLM‐powered applications/agents, tool use, orchestration, retrieval (RAG), prompt and safety engineering, evaluation and telemetry. Proficient knowledge of cloud‐native engineering: containers (GKE/Cloud Run), Terraform/IaC, CI/CD, automated ...

maintain robust automation solutions that streamline workflows and enhance operational efficiency. Collaborate with cross-functional teams to extend existing agent-based solutions and RAG implementations. Take ownership of the full software lifecycle: build, deploy, monitor, and tune solutions in a live environment. Ensure production maturity by transitioning solutions from proof … practises. Production Focus : A solid engineering mindset with the capability to extend existing automation rather than starting from scratch. Desired Qualifications: Experience with RAG architecture implementation and vector databases. Exposure to Azure AI and OpenAI technologies. Familiarity with enterprise workflow automation and agentic AI frameworks. Financial Services Adecco ...

logging, and safe rollout patterns Preferred Qualifications, Capabilities, and Skills Experience developing generative AI applications, AI agents, vector search, and retrieval‐augmented generation patterns Experience building AI agents using frameworks such as LangChain, CrewAI, LangGraph, or similar orchestration platforms Experience operating or integrating serving … platforms such as KServe, Ray Serve, NVIDIA Triton Inference Server, Text Generation Inference (TGI), alongside vLLM/llm‐d Familiarity with Amazon SageMaker JumpStart, SageMaker Endpoints, and Amazon Bedrock for managed model hosting Experience with online LLM quality monitoring (e.g., hallucination, toxicity, drift detection) and tracing via OpenTelemetry ...

Copilot deployments, including security, prompt design and adoption tracking Help design, prototype, and test AI solutions, including Large Language Model (LLM) integrations, retrieval-augmented generation, agentic workflows and structured-output patterns Build well-scoped components and ship them through GitHub and Azure DevOps pipelines ...

Engineer to design, build, and deploy production-ready Generative AI systems. Role You will own the full lifecycle of GenAI applications, working with LLMs, RAG architectures, and agentic frameworks to deliver scalable, business-focused solutions. Responsibilities Build and deploy GenAI and RAG systems Develop agentic AI workflows Design prompts … clients and technical teams Requirements 1-3 years deploying LLM/GenAI systems in production Strong Python skills Experience with cloud platforms Knowledge of RAG, vector databases, and LLM frameworks Git and CI/CD experience Experience with LangChain and LangGraph AWS experience IT/Technology-related university degree (minimum ...

teams. Design and deliver Voice AI/Agentic IVR solutions leveraging: Google CES/CXAS, Dialogflow CX/CCAI Vertex AI (LLMs, RAG, agent frameworks) Define and implement enterprise data architecture for Voice AI: Conversation data pipelines (real-time + batch) Integration with data lakes, warehouses (BigQuery) Customer … contextual data enablement Build RAG-based knowledge systems integrating structured and unstructured banking data. Architect data-driven decisioning for voice agents (personalization, next-best action, fraud detection signals). Ensure integration with core banking, CRM, and analytics platforms . Establish data governance, lineage, quality, and compliance frameworks (GDPR ...