101 to 125 of 153 Retrieval-Augmented Generation Jobs in London

solving some of the most exciting challenges and problem solving in enterprise AI rollout, spanning enterprise data pipelines, multi-agent orchestration/workflows and RAG/SLM finetuning. Responsibilities Lead the technical solution design and implementation of large-scale Agentic and Knowledge AI solutions for key enterprise clients. … solution delivery through reusable assets, frameworks, and documentation. Champion observability, monitoring, versioning and telemetry to ensure trustworthy and auditable AI agents. Stay current on RAG, LLM/SLM advancements, Agentic AI tooling, vector/graph databases, retrieval optimizations, multi-modal systems, evaluation frameworks, GPU/Infra trends, fine ...

extend platform components—APIs, tooling, and bespoke logic Architecture & Standards Architect robust, scalable, and compliant Agentic AI solutions across industries Lead multi-agent orchestration, RAG pipelines, and LLM/SLM integration design Champion observability, telemetry, and auditable AI standards Build and maintain reusable frameworks and asset libraries Team & Product Help …/Vue, SQL, REST/GraphQL DevOps proficiency: Docker, Kubernetes, CI/CD, and major cloud platforms Expertise in LLMs, Prompt Engineering, Vector DBs, RAG pipelines, and Agentic orchestration frameworks Agentic/Integrations: MCP, Salesforce/SAP/Other Excellent communication with both technical and executive stakeholders Mentorship capability ...

TypeScript Contribute to scalable, distributed systems and cloud architecture (AWS) Work with structured and unstructured data across varied storage solutions Build and integrate RAG pipelines and AI-driven workflows Implement LLM integration patterns and multi-step orchestration Collaborate with cross-functional teams to deliver robust, high-quality systems What They ...

enterprise clients. We work with organisations to understand their workflows, identify where AI can automate or augment work, and build practical systems across LLMs, RAG, workflow automation, document intelligence, operational copilots, data extraction, and enterprise integrations. Our projects move quickly, so delivery is critical. We need someone who can help ...

proof-of-concept role. You will be responsible for delivering secure, resilient and scalable AI-enabled applications that consume standardised GenAI services, including LLMs, RAG, summarisation and extraction capabilities. You will work closely with GenAI Engineers, Platform Engineers, Product, Architecture and Business Delivery teams to turn business problems into robust … responsibilities: * Design, build and maintain AI-enabled applications using enterprise GenAI services* Develop production-grade microservices and/or full-stack applications* Integrate LLM, RAG, summarisation and extraction services into secure, scalable applications* Own end-to-end delivery, including development, CI/CD, deployment, monitoring and incident resolution* Build ...

/or data platforms at scale Experience in a senior technical or leadership role (3+ years) Strong understanding of modern AI approaches, including LLMs, RAG, and orchestration Knowledge of cloud environments, security, and compliance considerations Morgan Hunt is a multi-award-winning recruitment business for interim, contract and temporary recruitment ...

scalable, and genuinely useful in production environments. You'll work on some of the most technically demanding AI challenges in industry: multi-agent systems, RAG pipelines, agentic workflows, and robust evaluation frameworks, all at enterprise scale. What You'll Be Doing Designing and building production-grade AI systems that integrate … LLMs, RAG pipelines, vector databases, and agentic frameworks Creating evaluation and observability frameworks to measure, monitor, and continuously improve system performance, accuracy, and reliability Implementing and maintaining retrieval systems, including ingestion pipelines, chunking strategies, and advanced techniques such as HyDE Building and owning production AI applications: clean code ...

Data Factory, Azure Data Lake Storage, Azure SQL, Azure Functions, Azure Key Vault, Azure AI Search and Azure OpenAI where required. Support AI and RAG use cases by preparing structured and semi-structured data for retrieval, grounding, metadata enrichment and agent workflows. Implement data quality checks, validation rules … Microsoft DP-203 and/or DP-700 certification, or equivalent practical experience. Experience with Azure AI Search, Azure OpenAI, Azure AI Foundry or RAG-style data preparation. Experience integrating Microsoft 365, SharePoint, Teams, Dynamics, Salesforce, E-commerce or finance systems. Knowledge of OneLake shortcuts, Delta Lake, medallion architecture ...

Data Factory, Azure Data Lake Storage, Azure SQL, Azure Functions, Azure Key Vault, Azure AI Search and Azure OpenAI where required. Support AI and RAG use cases by preparing structured and semi-structured data for retrieval, grounding, metadata enrichment and agent workflows. Implement data quality checks, validation rules … Microsoft DP-203 and/or DP-700 certification, or equivalent practical experience. Experience with Azure AI Search, Azure OpenAI, Azure AI Foundry or RAG-style data preparation. Experience integrating Microsoft 365, SharePoint, Teams, Dynamics, Salesforce, E-commerce or finance systems. Knowledge of OneLake shortcuts, Delta Lake, medallion architecture ...

include AI sales assistants, underwriting automation, internal summarisation systems, and workflow efficiency tools. Key Responsibilities • Build and deploy production-grade AI applications • Develop LLM, RAG, and agentic AI systems • Deploy applications into GCP environments • Work closely with cross-functional business stakeholders • Improve scalability, reliability, and AI deployment workflows • Build APIs … days per week in London office • Contract: 12-month FTC (maternity cover) • Tech stack: Python, GCP, APIs, Docker, Kubernetes, CI/CD, LLMs, RAG, LangChain/LlamaIndex • Sponsorship: Cannot sponsor Interested? Please apply below. ...

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 ...

this is the clearest indicator of someone who has shipped LLM systems in production. • Deep, current LLM engineering practice. System-level prompt design, RAG, structured generation, fine-tuning trade-offs (SFT, DPO, LoRA), and working knowledge of the frontier model landscape. • LLM safety and security. Prompt injection mitigation ...

London. Known for their entrepreneurial culture and deep expertise across financial services, this is an exceptional opportunity to architect and deliver next-generation AI systems at the heart of some of the world's most complex financial institutions. You'll take a hands-on leadership role designing … that bring together multi-modal LLMs. Building agentic workflows that connect AI agents to live data sources and APIs, drawing on prompt engineering and RAG to drive accuracy and relevance Optimising and shipping large language and multi-modal models into production, balancing performance, latency, and reliability at enterprise scale Developing ...

OpenAI, Azure ML and Copilot Studio. Develop and manage CI/CD, LLMOps, and MLOps pipelines for Generative AI applications. Design and deploy GenAI, RAG and intelligent agent solutions across enterprise systems. Implement Infrastructure as Code (Terraform) and secure cloud environments following best practices. Support AI experimentation, model fine-tuning … across all AI initiatives. Required Experience Strong experience with Azure AI services, Azure OpenAI and AI infrastructure engineering. Hands-on expertise with Generative AI, RAG architectures, NLP and agentic workflows. Experience building secure CI/CD, LLMOps, and MLOps pipelines. Knowledge of Terraform, cloud security, APIs, and enterprise integrations. Familiarity ...

across products and enterprise transformation initiatives. What You'll Do Design and deploy AI agents and agentic workflows powered by LLMs Build systems using RAG, reasoning, planning, memory, and tool orchestration Develop multi-step AI solutions capable of autonomous decision-making and tool usage Work with MCP-style architectures … applications into production Hands-on expertise with LangChain, LangGraph, or similar frameworks Demonstrable experience building Agentic AI systems and AI agents Strong understanding of RAG architectures and LLM optimisation Experience with FastAPI, MCP/FastMCP, or similar technologies Familiarity with cloud-native AI deployments and data-driven applications Important Applications ...

PrivateLink for cross-cloud data connectivity. AI Readiness : Practical experience architecting data infrastructure for AI/ML consumption - vector databases, embedding stores, and RAG pipeline integration. Soft Skills: Strong interpersonal skills; ability to translate complex data architecture into clear language for Business Analysts and non-technical stakeholders. Duties Data Modelling … warehouse scheduling strategies to reduce operational data spend. AI Readiness: Architect data stores purpose-built for LLM consumption - including vector databases, embedding pipelines, and RAG-compatible data structures that will serve as the foundation for Bestway's AI product layer. Data Contracts : Partner with Business Analysts to formally define ...

multi-modal LLMs (text, image, audio, video), design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG, optimise and deploy large language and multi-modal models with a focus on performance and latency and build scalable MLOps pipelines and full-stack applications … Langsmith, MCP (Model Context Protocol), bias mitigation techniques Apply now to find out more about this Backend Software Engineer/Developer (Python LLM MLOps RAG MCP) opportunity. ...

for. What you'll be working on as an AI Engineer - LLM & Agentic Systems: Designing and building AI agents and agentic workflows - combining LLMs, RAG, reasoning, memory and tool orchestration to solve real, complex business problems. Owning delivery end-to-end - from initial exploration through to production deployment, integration … with clear, real-world examples you can speak to confidently. Hands-on experience building AI agents including tool use, orchestration and multi-step reasoning - RAG systems that actually deliver, not just proofs of concept. Strong Python skills and solid machine learning foundations - able to write clean, production-grade code with ...

based workflows, integrating AI platforms, and delivering scalable cloud-native solutions. Responsibilities AI Agent Engineering Design and implement AI agents, including: Retrieval (RAG) Orchestration workflows Tool/function invocation Policy-based routing Build evaluation frameworks for accuracy, latency, and reliability Implement observability and monitoring for agent lifecycle … engineering experience Strong experience with cloud-native systems (APIs, microservices, containers, serverless) Experience building and deploying AI/LLM-based systems in production (agents, RAG, orchestration) Proficiency in Python, Java, or similar backend languages Experience with: CI/CD pipelines Infrastructure as code Monitoring and observability tools Hands-on experience ...

Technical Project Manager - London/Hybrid - Fluent French - AI Delivery/RAG/Multi-Agent Systems - £40,000 - £60,000 The Role An ambitious and fast-growing AI consultancy are looking for a Project Manager with strong experience in AI to lead client engagements from discovery through to delivery. Working … concepts into practical business solutions. As a Project Manager here, you'll have the opportunity to work on cutting-edge AI initiatives involving RAG, multi-agent systems, modern LLM frameworks, and production AI deployments. You'll play a major role in shaping how projects are delivered and influence both technical ...

processing) AWS Bedrock, SageMaker, or similar managed AI services Observability frameworks for LLM systems (Langfuse, Arize, LangSmith) RAG pipelines, vector databases, or retrieval-augmented systems CI/CD automation; infrastructure-as-code (Terraform, CloudFormation) Why This Matters You're not building features. You're building ...

into practical AI solutions. Responsibilities Building, prototyping and deploying AI/LLM products Working with enterprise customers and internal engineering teams Using Python, LLMs, RAG, embeddings and vector databases Working with tools such as LangChain, LlamaIndex, OpenAI, Azure OpenAI or Anthropic Translating ambiguous business problems into working technical solutions Qualifications … Strong Python engineering experience Production experience with AI/LLM systems Hands-on RAG, prompt engineering, embeddings or vector database experience Confidence working with technical and non-technical stakeholders Comfortable in a client-facing, delivery-focused role Required Skills Strong Python engineering experience Production experience with AI/LLM systems ...

data with advanced machine learning and synthetic intelligence. The Role Design, build, and deploy Generative AI and LLM-based solutions for synthetic data generation and data augmentation Develop and validate statistical and machine learning methodologies to ensure data quality, reliability, and trust Work closely with Product and Engineering … datasets and collaborating with engineering teams Confidence explaining methodology, limitations, and impact to a broad range of stakeholders Exposure to synthetic data, prompt engineering, RAG, or cloud-based data platforms is beneficial but not essential ...

growth of the company. You’ll take responsibility for key parts of the AI stack, including: Architecting and deploying multi-agent systems Building scalable RAG pipelines and retrieval systems Creating evaluation frameworks (performance, safety, reliability) Shipping AI-driven products used in real-world enterprise settings Alongside this … design: orchestration, memory, deployment, monitoring – Exposure to tools such as LangGraph, ReAct, CoT — or building similar systems from scratch – Familiar with PyTorch/TensorFlow, RAG architectures, vector databases, modern cloud infra – Experience in startup or consulting environments is a plus – Comfortable working autonomously in fast-moving, sometimes ambiguous settings With ...

reusable agent components and playbooks Proactively surface new automation opportunities across the business Key Skills Python & LLM agent frameworks (LangChain, CrewAI, LlamaIndex) Prompt engineering & RAG pipelines Business analysis & stakeholder management Process mapping & workshop facilitation Microsoft 365 & Microsoft Copilot No-code/low-code tooling (Zapier, Make) Desirable Skills Experience … etc. Strong enough technically to assess feasibility and scope what is buildable; commercially sharp enough to prioritise what is worth building. Familiarity with LLMs, RAG pipelines, tool/function calling, and integrating AI into real business workflows. Proven ability to lead discovery workshops and translate complex business problems into clear ...