301 to 325 of 400 Retrieval-Augmented Generation Jobs in the UK

NLP PEOPLE is seeking a Machine Learning Engineer in London (Hybrid) with a focus on NLP and LLMs. You will enhance retrieval systems and shape technical direction. The ideal candidate will have 5+ ...

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 ...

horizon memory and knowledge infrastructure that will allow agents to learn, recall, and reason over vast, evolving enterprise contexts. This is not about simple RAG; it’s about pioneering the future of agent memory (episodic, semantic, and procedural). Innovate in Search & Retrieval: Develop state ...

extract patterns from one-off work and turn them into reusable assets for others.**Applied AI and Agentic Systems*** Experience building with LLMs, agents, RAG, tool use, workflow orchestration, or automation systems.* Ability to reason about multi-agent, human-in-the-loop, and enterprise integration patterns.* Comfort debugging agent behavior ...

Location: UK - Hybrid/Remote with client travel Salary: £90,000 - £110,000 + bonus and benefits Skills: Enterprise AI Transformation, Generative AI, LLMs, RAG, AI Agents, Workflow Automation, AI Prototyping, Technology Consulting, Discovery Workshops, Pre-Sales, Proposition Development The opportunity We are working with a growing technology and transformation ...

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 ...

governance across multiple accounts, while communicating effectively with business stakeholders. The role requires hands-on Azure Foundry and OpenAI experience, strong modeling and RAG-based knowledge, and the ability to oversee secure, scalable AI workloads in regulated environments. #J-18808-Ljbffr ...

Senior AI Evangelist to lead design and delivery of Generative AI solutions for clients. You will architect end-to-end AI systems, including LLMs, RAG, multi-agent workflows, and MCP-based integrations, collaborating with cross‐functional teams to meet defined metrics. The role requires hands-on expertise with modern ...

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 ...

Significant engineering experience with cloud-native systems (APIs, microservices, containerization, serverless) Deep expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments Considerable experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models, including building abstraction layers to manage multi-provider pipelines ...

ingestion, storage, governance, analytics, model deployment, monitoring, and integration with enterprise applications. Understanding of generative AI solution patterns, such as retrieval‐augmented generation, enterprise search, intelligent assistants, document processing, content generation, and AI‐enabled workflow automation. Awareness of AI governance, responsible … Model Garden, Document AI, Gemini, or other Google Cloud data, analytics, API management, AI, or generative AI services. Experience designing retrieval‐augmented generation architectures using vector search, embeddings, enterprise data sources, access controls, and secure application integration patterns. Experience with MLOps, including model lifecycle ...

tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams. Applies knowledge … multiple modern programming languages including Python, Golang, TypeScript and similar technologies in an AWS/Cloud environment. Experience in the use of GPT, LLM, RAG, Gen AI, Prompt Engineering related technologies Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages ...

platform - including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimization, and other post-training and agentic techniques - enabling the next generation of AI-powered products, agents, automation, and personalization. We’re excited about you because you have... BSc, MSc, or PhD in Computer Science … internal platforms, or self‐serve infrastructure Experience building and deploying AI agents or MCP servers in production Experience with eval systems, LLM observability, tracing, RAG, search, or vector databases Diversity, Equity and Inclusion At the company, we know that a great workplace reflects the world around us and that true ...

platform and infrastructure engineering role - not a data science or ML engineering position. You'll own the runtime, infrastructure, and operational layers that RAG pipelines, LLM orchestration, vector search, and evaluation workflows run on, across AWS and Databricks. The focus is on building scalable, observable, secure, and cost-efficient platform … infrastructure (OpenSearch, Algolia, AWS Bedrock Knowledge Bases) and embedding pipelines Build and maintain CI/CD pipelines for inference services, retrievers, ingestion workflows, and RAG components Implement observability across AI workloads using CloudWatch, MLflow, and OpenTelemetry - covering latency, throughput, cost, and system health Apply secure-by-design principles including ...

qualifications. Tech focus: Python and AWS (or equivalents in Azure or GCP), with hands‐on work across classical ML and modern LLM/RAG systems using services like Amazon SageMaker and Bedrock. What you’ll do Partner with stakeholders across the business to explore high‐impact opportunities. Own the full … lifecycle: problem framing, data discovery, feature engineering, modelling, evaluation, deployment, monitoring, and iteration. Build and productionize LLM features where appropriate (retrieval‐augmented generation, evaluation, safety guardrails, cost/latency optimization) on AWS. Contribute to DS/ML standards: experimentation, model governance, documentation, and reproducibility. ...

financial reporting platform. Engineer Digital Integrated Agents for JTC’s client-facing digital products, enabling non-linear user journeys, content and dynamic UI generation, conversational AI-enabled analytics and reporting, and persona-aware hyper-personalisation services. Deliver the enterprise document extraction platform and agent supporting workflows across service … from prototype through governed production deployment and ongoing operation. Deep hands-on expertise in LLMs and agentic systems: prompt and context engineering, retrieval-augmented generation, tool/MCP orchestration, multi-agent workflows and evaluation frameworks. Experience with the Anthropic stack (Claude, Claude Code, agent ...

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 ...

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 ...

consecutive years at one employer, with experience more important than a specific title. Deep expertise in generative AI products, including retrieval‐augmented generation, agentic workflows, and their evaluation. Proven ability to independently drive product strategy and execution across multiple engineering organisations and external dependencies. ...

extract patterns from one‐off work and turn them into reusable assets for others. Applied AI and Agentic Systems Experience building with LLMs, agents, RAG, tool use, workflow orchestration, or automation systems. Ability to reason about multi‐agent, human‐in‐the‐loop, and enterprise integration patterns. Comfort debugging agent behavior ...

leaders to drive AI-enabled transformation across enterprises, leading engagements from discovery to execution and shaping AI strategy. You will translate GenAI, LLMs, RAG into actionable roadmaps, engage C-suite stakeholders, and contribute to revenue growth with strong consulting acumen. The role offers hybrid working across London, Manchester or Glasgow ...

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 ...