176 to 200 of 269 Retrieval-Augmented Generation Jobs in London

Security/Compliance (HIPAA, GDPR, NHS DTAC, SOC2) What You’ll Do Build highly scalable backend services and APIs Work on LLM-powered features (RAG pipelines, embedding workflows) Develop agentic document extraction systems for clinical PDFs Own backend reliability, performance, and security Work cross-functionally with product, frontend, and leadership ...

Security/Compliance (HIPAA, GDPR, NHS DTAC, SOC2) What You’ll Do Build highly scalable backend services and APIs Work on LLM-powered features (RAG pipelines, embedding workflows) Develop agentic document extraction systems for clinical PDFs Own backend reliability, performance, and security Work cross-functionally with product, frontend, and leadership ...

Ability to build responsive interfaces and manage complex backend logic. Excellent problem-solving and time management skills. Bonus Skills: Experience with Azure, Docker, LangChain, RAG models, and pandas. What’s on Offer Transparent salary framework and twice-yearly promotion opportunities . 25 days annual leave plus three extra days ...

Ability to build responsive interfaces and manage complex backend logic. Excellent problem-solving and time management skills. Bonus Skills: Experience with Azure, Docker, LangChain, RAG models, and pandas. What’s on Offer Transparent salary framework and twice-yearly promotion opportunities . 25 days annual leave plus three extra days ...

NoSQL databases to build scalable, event-driven systems. Design and optimise APIs that serve our mobile and web products, including partner integrations. Implement efficient RAG AI backend systems for introducing advanced LLM based features Collaborate with product managers, data engineers, and frontend developers to deliver new features end to end. ...

NoSQL databases to build scalable, event-driven systems. Design and optimise APIs that serve our mobile and web products, including partner integrations. Implement efficient RAG AI backend systems for introducing advanced LLM based features Collaborate with product managers, data engineers, and frontend developers to deliver new features end to end. ...

storage and search systems (e.g. pgvector, Pinecone, Azure Search), as well as experience working with graph technologies like Neo4j Practical understanding of retrieval-augmented generation pipelines and how to implement structured outputs or link models to graph-based knowledge systems Track record of optimising ...

storage and search systems (e.g. pgvector, Pinecone, Azure Search), as well as experience working with graph technologies like Neo4j Practical understanding of retrieval-augmented generation pipelines and how to implement structured outputs or link models to graph-based knowledge systems Track record of optimising ...

solutions across various sectors, predominantly financial services . You will work on a diverse mix of projects, ranging from complex Generative AI architectures (RAG, Agents) to Machine Learning problems (forecasting, classification, anomaly detection). The ideal candidate will have strong software engineering fundamentals alongside deep ML knowledge. Role: Architect & Build … GenAI Systems: Design and deploy advanced RAG and GraphRAG applications ML Implementation: Develop and maintain traditional machine learning models (Regression, Classification, Clustering, Time-Series) to solve structured data problems Agentic Workflows: Build multi-agent systems using frameworks like LangGraph, AutoGen, or similar to automate complex analysis tasks Evaluation & Observability: Implement ...

solutions across various sectors, predominantly financial services . You will work on a diverse mix of projects, ranging from complex Generative AI architectures (RAG, Agents) to Machine Learning problems (forecasting, classification, anomaly detection). The ideal candidate will have strong software engineering fundamentals alongside deep ML knowledge. Role: Architect & Build … GenAI Systems: Design and deploy advanced RAG and GraphRAG applications ML Implementation: Develop and maintain traditional machine learning models (Regression, Classification, Clustering, Time-Series) to solve structured data problems Agentic Workflows: Build multi-agent systems using frameworks like LangGraph, AutoGen, or similar to automate complex analysis tasks Evaluation & Observability: Implement ...

quality controls. Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC). Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures. Familiarity with LLMOps tooling (LangSmith, LangChain, LangGraph). Understanding of model evaluation, validation, and production monitoring. Strong problem-solving skills and ability to communicate … security clearance; no sponsorship provided. Desirable: Advanced LLM techniques: agents, tool use, and agentic workflows. Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications. Experience with feature stores (Feast, AWS Feature Store). Containerisation (Docker) and orchestration (Kubernetes, ECS). Infrastructure as Code (Terraform, CloudFormation). Large-scale data ...

applications using Copilot Studio (Full), Power Platform, Dynamics 365, and Azure AI; establish security, governance, and performance baselines. Design and implement LLM-powered solutions (RAG, prompt engineering, grounded generation) with data governance, telemetry, and quality monitoring ( LLMOps ). Integrate Microsoft 365 and Dynamics 365 with enterprise systems ...

applications using Copilot Studio (Full), Power Platform, Dynamics 365, and Azure AI; establish security, governance, and performance baselines. Design and implement LLM-powered solutions (RAG, prompt engineering, grounded generation) with data governance, telemetry, and quality monitoring ( LLMOps ). Integrate Microsoft 365 and Dynamics 365 with enterprise systems ...

What We're Looking For Must-Haves: 4+ years experience writing production ready code for machine learning systems 2+ years experience developing conversational AI, RAG, agentic systems or LLM-based products Familiarity with RAG orchestration frameworks such as LangChain or LlamaIndex.2+ Experience with production optimisation for RAG systems, including latency ...

What We're Looking For Must-Haves: 4+ years experience writing production ready code for machine learning systems 2+ years experience developing conversational AI, RAG, agentic systems or LLM-based products Familiarity with RAG orchestration frameworks such as LangChain or LlamaIndex.2+ Experience with production optimisation for RAG systems, including latency ...

What We're Looking For Must-Haves: 4+ years experience writing production ready code for machine learning systems 2+ years experience developing conversational AI, RAG, agentic systems or LLM-based products Familiarity with RAG orchestration frameworks such as LangChain or LlamaIndex.2+ Experience with production optimisation for RAG systems, including latency ...

applications providing cutting-edge scientific tooling to scientists Shape the AI strategy and technology stack Develop AI features leveraging various methodologies (e.g., LLMs, RAG, traditional ML) Design and implement data strategies for AI development and training Requirements 4+ years' experience across Fullstack development (Python/Modern JavaScript (React ...

iterative prototyping across multidisciplinary teams. Strong foundation in software development with C# and TypeScript. Experience with AI/LLM concepts (e.g., prompt engineering, RAG). Analytical mindset for assessing sufficiency (relevance, completeness, freshness) and mitigating risks like hallucinations. Focus on Clean Architecture and Clean Code principles. Familiarity with Enterprise Design ...

systems, mentor engineers, and stay hands-on in Python/PyTorch. Own the model lifecycle: From fine-tuning and RLHF/DPO to designing RAG pipelines. Build smarter moderation: Develop classifiers and safety systems that go beyond simple filters. What We’re Looking For Proven experience shipping AI/ ...

systems, mentor engineers, and stay hands-on in Python/PyTorch. Own the model lifecycle: From fine-tuning and RLHF/DPO to designing RAG pipelines. Build smarter moderation: Develop classifiers and safety systems that go beyond simple filters. What We’re Looking For Proven experience shipping AI/ ...

systems, mentor engineers, and stay hands-on in Python/PyTorch. Own the model lifecycle: From fine-tuning and RLHF/DPO to designing RAG pipelines. Build smarter moderation: Develop classifiers and safety systems that go beyond simple filters. What We’re Looking For Proven experience shipping AI/ ...

experience building and deploying real-world products Strong understanding of modern AI systems, including LLMs, multimodal models, agents, and supporting tooling (e.g. LangChain, RAG pipelines, SFT/RL fine-tuning) Solid infrastructure experience, including cloud platforms, containerization, and relational or graph databases Proven ability to build independently, move quickly ...

experience building and deploying real-world products Strong understanding of modern AI systems, including LLMs, multimodal models, agents, and supporting tooling (e.g. LangChain, RAG pipelines, SFT/RL fine-tuning) Solid infrastructure experience, including cloud platforms, containerization, and relational or graph databases Proven ability to build independently, move quickly ...

growing AI team , contribute to cutting-edge projects, and develop your skills with mentorship from senior engineers. You'll work on AI-powered applications, RAG pipelines, and model fine-tuning , solving real business problems. About the Role Design, implement, and fine-tune LLMs and generative AI solutions (OpenAI, Anthropic Claude … Gemini, open-source models) Build and optimize RAG pipelines , vector databases, and prompt engineering strategies Develop AI-powered applications integrating LLMs with APIs, agents, and workflows Deploy and monitor AI models on cloud platforms (Azure preferred; AWS/GCP acceptable) Collaborate with senior engineers and cross-functional teams to deliver ...

identify AI integration opportunities for productivity, quality, or innovation gains. Design, code, train, and test AI models tailored to use cases (e.g., NLP, CV, RAG, forecasting, etc.). Perform effort estimation and model validation and monitor deployment success and cost-performance trade-offs. Collaborate closely with local technical leads while … Learning, Deep Learning, Natural Language Processing, Computer Vision, Generative AI, Reinforcement Learning, LLMs (e.g., GPT, Claude, Mistral, LLaMA, DeepSeek, etc.). Agent-based architectures, RAG, prompt engineering, chatbots, classification, summarization, speech-to-text, image understanding. Cloud platforms (AWS, Azure, GCP). ML Ops tools and deployment workflows. AI-assisted development ...