1 to 25 of 78 Remote/Hybrid Retrieval-Augmented Generation Jobs in London

enterprise-scale AI projects, leveraging the latest Generative AI technologies including LLMs, Agentic AI and Retrieval-Augmented Generation (RAG), while collaborating with data scientists, engineers and senior business stakeholders. The Role As an AI Engineer, you'll take ownership of designing and delivering … Doing Designing and developing enterprise AI and Machine Learning solutions Building Agentic AI frameworks and Retrieval-Augmented Generation (RAG) applications Developing intelligent reporting, recommendation and forecasting solutions Working with Large Language Models (LLMs) and foundation models Deploying production-ready machine learning models into cloud ...

solutions using modern Azure technologies and cloud-native architecture. Integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and Agentic AI capabilities into business applications. Develop responsive frontend applications alongside robust APIs and backend services to create seamless user experiences. Work closely with Product … Services and cloud-native application development. Experience implementing AI solutions including LLM integration, prompt engineering, Retrieval-Augmented Generation (RAG) and vector databases. Experience working with SQL and NoSQL databases, with knowledge of platforms such as SQL Server, Snowflake, OneLake or similar data platforms. Strong ...

evolve the enterprise AI platform that powers AI products across the company. Develop scalable AI services supporting Agentic AI, Retrieval‐Augmented Generation (RAG), embeddings, vector search, model serving, and intelligent automation. Build orchestration layers that transform structured and unstructured enterprise data into reusable … Hands‐on experience building applications powered by Large Language Models (LLMs). Experience building Model Context Protocol (MCP) and Retrieval‐Augmented Generation (RAG) solutions, making use of embeddings, vector databases, and modern LLM orchestration frameworks. Experience building or contributing to agentic AI systems, intelligent ...

Role We're scaling the backend systems powering our AI-driven product suite, including retrieval-augmented generation (RAG) pipelines, real-time inference APIs, and vector search infrastructure. You'll own the services that sit between our LLM providers and our customer-facing products, focusing … What You'll Do: Design and maintain APIs serving LLM-powered features (chat, search, agentic workflows) to 500k+ monthly active users Build and optimise RAG pipelines, including chunking strategies, embedding generation, and vector store management Architect event-driven microservices using Kafka/SQS for async processing of high ...

engineers who have built AI solutions around document intelligence, enterprise search, knowledge management, NLP or Retrieval-Augmented Generation (RAG), rather than purely research-focused AI. Key Responsibilities Design, build and deploy production-ready LLM and Machine Learning solutions using Azure Databricks, Azure Machine Learning … Foundry Good understanding of MLOps and LLMOps Excellent Python engineering skills with experience using frameworks such as LangChain, LangGraph, PyTorch and Pydantic Experience with RAG, vector search, embeddings, prompt engineering and enterprise retrieval architectures Experience building AI solutions within document-heavy environments such as legal, financial services, insurance ...

with big data technologies (e.g. Hadoop, Hive, Spark). Experience with generative AI, LLMs, or retrieval-augmented generation (RAG). Exposure to Agentic AI concepts, including autonomous agents, tool use, and orchestration frameworks. Experience applying machine learning and AI to scientific ...

agentic architectures. Good understanding of modern AI concepts and practices, including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Prompt Engineering AI Guardrails AI Evaluation Frameworks Experience with AI frameworks such as Agent Development Kit (ADK), LangChain, LangGraph, CrewAI, or similar. Experience working with ...

enterprise environment. Driving build versus buy evaluations and recommending appropriate technologies. Delivering solutions including retrieval-augmented generation (RAG), agentic AI, automation, and intelligent decision-support tools. Working closely with engineering, security, governance, and business stakeholders. Navigating complex and ambiguous problem spaces to identify practical … fundamentals and experience building scalable applications. Experience making architecture and technology decisions within enterprise organisations. Strong knowledge of modern AI engineering practices, including LLMs, RAG, agentic workflows, and MLOps concepts. Experience working with cloud platforms, ideally AWS. Ability to balance innovation with risk, governance, and operational requirements. Strong stakeholder management ...

solution approaches across the modern AI stack, including Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), Vector Databases and MLOps. Support clients in navigating cloud, security, data governance and operating model considerations required for enterprise AI adoption. Communicate complex machine learning ...

modern AI technologies and concepts, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases AI Solution Architecture MLOps Principles AI Governance and Risk Considerations Candidates are not expected to be hands-on developers but should be capable ...

technology teams to optimise semantic models for AI readiness. Apply data science, machine learning, NLP, and advanced analytics techniques to enhance insight generation and anomaly detection. Contribute to the organisation's long-term Data & AI strategy, influencing senior stakeholders and executive leadership. Establish best practices, standards, and governance … shape direction and define solutions. Desirable Experience Microsoft Copilot, Azure OpenAI, or similar AI platforms. Retrieval-Augmented Generation (RAG) and semantic grounding techniques. Executive-level analytics solutions and trusted AI implementations. Highly regulated or data-governed environments. What We Offer Opportunity to influence enterprise ...

understanding of the modern AI ecosystem, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases MLOps Experience leading the implementation of enterprise-scale AI solutions and being accountable for delivery outcomes. Knowledge of cloud platforms such ...

Apply advanced techniques including optimisation, forecasting, statistical modelling and AI Develop LLM-based solutions, including: Retrieval-Augmented Generation (RAG) Fine-tuning and prompt engineering Agent-based workflows Work with large and complex datasets, both structured and unstructured Write clean, scalable Python code for model … Pandas, NumPy, SciPy or similar) Solid grounding in statistics, probability and data analysis AI & LLM Experience Hands-on experience with large language models, including: RAG pipelines Fine-tuning approaches Agent-based architectures A practical understanding of how to apply LLMs to real-world use cases Tools & Engineering Experience with model ...

Guide architecture across teams, helping reduce complexity and establish common patterns. Partner with AI and Retrieval teams to build scalable search and RAG capabilities. Lead complex cross-team technical initiatives from design through production. Improve platform reliability, scalability, observability, and developer experience. Contribute hands-on to critical technical … with cloud infrastructure (AWS), Kubernetes, APIs, and modern backend development. Familiarity with AI-powered systems, Retrieval-Augmented Generation (RAG), search platforms, or vector databases. Strong programming experience in Python or another modern backend language. Comfortable influencing technical direction without direct authority. Excellent communication skills ...

delivered across the organization. Key Responsibilities: Lead the design and build of end-to-end generative AI applications using LangGraph, including agentic workflows, RAG pipelines, and LLM-integrated services. Define and drive architecture for scalable, secure, reliable, and maintainable AI solutions deployed in production. Develop robust, well-tested backend APIs ...

deploy AI‐powered applications including chatbots, copilots, document intelligence, and decision‐support tools for insurance use cases.* Implement Retrieval‐Augmented Generation (RAG) patterns using structured and unstructured insurance data (policies, submissions, bordereaux, claims documents).* Build LLM‐based workflows and agents using platforms such … experience with ChatGPT/OpenAI APIs and/or Anthropic Claude.* Practical experience with prompt engineering, system prompts, and evaluation techniques.* Experience implementing RAG architectures, vector databases, and semantic search.**Cloud & Platforms*** Strong experience with Google Cloud Platform (GCP), ideally Vertex AI.* Experience deploying services using Docker/containerised workloads. ...

implementing end-to-end AI/ML solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance and best practices * Translating business requirements into cloud-native AI and data architectures across Azure ...

experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems Experience designing and scaling low-latency, customer-facing ...

MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge of Generative AI, LLMs, prompt engineering and RAG architectures Experience with LLMOps tools such as LangChain, LangSmith or LangGraph Strong understanding of model monitoring, validation and governance Excellent communication and stakeholder management skills Ability ...

Role We're scaling the backend systems powering our AI-driven product suite, including retrieval-augmented generation (RAG) pipelines, real-time inference APIs, and vector search infrastructure click apply for full job details ...

structured, semi-structured and unstructured data OR 5+ years ML Engineering or AI Engineering deploying, promoting and serving ML models, building feature stores, building RAG chatbot or other AI systems Hands on, working, knowledge of Databricks ML and Gen AI features is required Expertise in software engineering or DevOps concepts ...

technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience ...

individual demos.Understanding of Azure security and identity controls as they apply to AI workloads: managed identities, private endpoints, and data residency.Develop and deploy RAG-based knowledge systems using Azure AI Search, Azure OpenAI Service, and relevant orchestration frameworks (LangChain, Semantic Kernel, or Prompt Flow).Design and implement AI agent architectures ...

based microservices for scalable, high-throughput architectures* Experience in cybersecurity, SIEM, SOAR, or adjacent security domains* Hands-on experience with LLM integration, prompt engineering, RAG pipelines, or agentic AI frameworks#LI-GO1#LI-HYBRID **Benefits of Working at CrowdStrike:*** Market leader in compensation and equity awards* Comprehensive physical and mental wellness programs ...

5+ years experience within software development and AI related rolesStrong experience building GenAI/Applied AI solutionsHands-on with LLMs, AI Agents, Agentic Workflows & RAG Proficiency in Python (TypeScript beneficial)Full-stack development with React, Next.js or SvelteAPI and backend development, including scalable microservicesExperience with SQL, NoSQL and Vector DatabasesCloud ...