1 to 25 of 120 Remote/Hybrid Retrieval-Augmented Generation Jobs in London

learning and large language models (LLMs) using frameworks such as PyTorch, TensorFlow, and Keras. Develop Retrieval-Augmented Generation (RAG) applications using LangChain, Hugging Face, and LlamaIndex. Implement and optimize vector database, semantic search, and hybrid search solutions for AI-powered applications. Perform model fine … model repositories Proficiency in LangChain and LlamaIndex for building AI-powered workflows Experience implementing Retrieval-Augmented Generation (RAG) frameworks Knowledge of Vector Databases and Hybrid Search techniques Strong understanding of Natural Language Processing (NLP) concepts and applications Experience with data processing, transformation, and feature ...

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 ...

Machine Learning solutions for customer-specific use cases. Build AI assistants, copilots, intelligent automation, and retrieval-augmented generation (RAG) applications. Design and integrate AI workflows with enterprise systems, databases, APIs, and business applications. Fine-tune prompts, optimize AI workflows, and improve model performance. Deploy … regulated industries such as Healthcare, Financial Services, Insurance, Telecom, or Manufacturing. Knowledge of AI governance, responsible AI, security, and compliance frameworks. Experience implementing RAG architectures and enterprise AI assistants. Exposure to AI observability, evaluation frameworks, guardrails, and monitoring platforms. Experience with Agentic AI and Multi-Agent Systems. Relevant certifications ...

language models across text, image, audio, and videoDesign and implement agentic workflows using prompt engineering, Retrieval-Augmented Generation (RAG), APIs, and enterprise data integrationsFine-tune, optimize, and deploy large language and multi-modal models with a focus on scalability, reliability, and low-latency performanceBuild … problem-solving skills within agile delivery environmentsBonus Points ForExperience building AI agent frameworks or autonomous orchestration platformsKnowledge of vector databases, semantic search, and advanced RAG architecturesExperience with cloud platforms such as AWS, Azure, or GCP for AI workloadsFamiliarity with financial services, banking, or regulated enterprise environmentsExposure to AI governance, model ...

tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic. Building retrieval-augmented generation (RAG) prototypes with vector stores and knowledge graphs. Developing and testing agentic architectures through our own Genie Platform – enabling AI agents that reason, retrieve, and act across … language suited to AI system development and data workflows. Experience integrating models with APIs, data sources, or production systems. Curiosity about LLMs, RAG pipelines (Graph & Vector based), and agent frameworks. Understanding of cloud-native (AWS/GCP/Azure) and DevOps/DevSecOps practices. A collaborative mindset and willingness ...

hands-on AI & Data Engineer to design, build and productionise AI agents, automation solutions, Retrieval-Augmented Generation (RAG) capabilities and data products supporting Balance Sheet Modelling . The role will work closely with business, architecture and technology teams to translate business use cases into … Umbrella. Remote First Working - Travel to local site when required. Key Responsibilities Design, develop and deploy production-ready AI agents and agentic workflows. Build RAG solutions, integrating Large Language Models (LLMs) with enterprise data and knowledge sources. Apply prompt engineering techniques to improve the accuracy, reliability and effectiveness ...

effectively as part of their day-to-day workflow. Bonus points for: Experience with retrieval-augmented generation (RAG) and vector databases (pgvector, Pinecone, or similar).Experience designing multi-agent systems and agent orchestration patterns. Familiarity with LLM observability tools (LangSmith, Langfuse, Arize, or similar ...

deployment of GenAI solutions, including LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG) for enterprise use cases. The ideal candidate has a strong foundation in machine learning and NLP, with hands‐on experience in modern GenAI tools and frameworks ...

architecture strategy and roadmap. Build scalable AI/ML and Agentic AI platforms spanning LLMs, retrieval-augmented generation (RAG), embeddings and semantic search. Lead on deployment, governance and integration patterns, advise clients on platform capability and implementation strategy, and partner with engineering, data, DevOps … business teams to deliver end-to-end solutions.**Tech environment**Python, LLMs (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes and GPU infrastructure.**What we're looking for**Proven enterprise AI or ML architecture design, strong cloud ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents.* Scale existing POCs to production-ready solutions for customer use.* Design and develop FullStack applications for both GenAI and non-GenAI projects. ...

Lineage, Master Data Management, and enterprise data catalogues. Strong knowledge of Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), LLM integration, Vector Databases, and AI governance frameworks. Significant experience leading technical pre-sales engagements and developing complex solution architectures. Demonstrable experience responding to large ...

cross-functional organizations.Deep knowledge of modern AI technologies including large language models (LLMs), agentic frameworks, retrieval-augmented generation (RAG), vector databases, and automation platforms — with the credibility to evaluate vendor claims and guide architectural decisions.Experience owning AI governance: building acceptable use policies, risk tiering ...

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 ...

generative AI solutions for scientific and knowledge-discovery applications. Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question answering, and evidence-grounded insight generation. Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks … skills and solid machine learning fundamentals. Experience working with large-scale text or content-rich datasets and modern AI/ML frameworks. Experience with RAG, semantic, vector, or hybrid search, along with experimentation and evaluation approaches that measure user impact. Familiarity with cloud platforms and modern software engineering practices. Strong ...

AWS. Translate business problems into secure, scalable, production-grade AI systems using Amazon Bedrock, retrieval-augmented generation (RAG), agentic workflows, and cloud-native AWS services. Drive architecture standards, model orchestration, governance, observability, and operational excellence across the GenAI lifecycle while collaborating with engineering, security … CloudWatch* Knowledge of scalable, secure, event-driven, and distributed system architectures* Experience integrating structured and unstructured enterprise data sources* Experience with RAG, fine-tuning, model evaluation, data privacy, ethical AI, and cross-functional stakeholder management is expected* Strong understanding of enterprise security architecture, IAM, encryption, and secure AI deployment practices ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

S3. Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data Version Control (DVC). Experience developing LLM or Generative AI applications, including RAG architectures and prompt engineering. Knowledge of LLMOps frameworks such as LangChain, LangGraph, or LangSmith. Experience taking ML models from experimentation into production environments. Strong communication ...

technical direction credibly and make sound architecture decisions. Demonstrated experience with AI/ML technologies, including LLMs, Retrieval Augmented Generation (RAG), agentic workflows, Natural Language Processing (NLP), and predictive analytics, and the discipline to run them reliably in production. Track record of building … Across TR: Legal, Data & Analytics, CTO, Product, CIO and wider CDO organisations, and Internal Audit. Technologies You’ll Work With LLMs and agentic frameworks RAG architectures AI agents and orchestration (e.g. LangChain/LangGraph) Python and modern data engineering Snowflake and governed semantic layers AWS/GCP cloud services Vector ...

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 ...

with Python and modern AI/ML frameworks such as PyTorch and/or TensorFlow . Deep understanding of LLMs, Generative AI, prompt engineering, RAG architectures and vector databases . Experience with frameworks and tooling such as LangChain, LangGraph or similar open-source AI toolkits . Experience fine-tuning, evaluating ...