51 to 75 of 102 Retrieval-Augmented Generation Jobs in the City of London

machine learning, and mathematical concepts Proven experience delivering production-grade data science solutions Hands-on experience with modern data science tooling, including LLMs/RAG approaches Advanced SQL skills Experience working in complex, enterprise-scale environments Strong written and verbal communication skills Ability to perform under technical interviews including live ...

gaming/fintech/FS) Curiosity for frameworks and agents that weren’t on GitHub yesterday Cloud + MLOps + vector search + RAG = all welcome. 🚀 Why this is a career move Board-level support — pace, budgets, expectations Chance to define AI engineering standards for a global brand Fast loops ...

build robust, scalable cloud-first backend systems. Contribute to infrastructure-as-code practices and DevOps tooling. Build and maintain LLM-powered features such as RAG pipelines for clinical information. Develop and optimise agentic document extraction workflows to process clinical PDFs, policies, and handbooks into structured formats. Collaborate closely with ...

Engineering skills (3 years+) Developed LLM architecture and deployed LLM applications Uptodate with current trends in AI Some experience with applying latest techniques like RAG architecture, GenAI, Parallel training etc The role is hybrid, with adhoc requirements to be on client premises (London) this could be between 1-3 days ...

core mathematical concepts Proven experience delivering production-grade data science solutions in complex environments Exposure to modern data science tooling, including LLMs and RAG-style approaches Advanced SQL skills Experience working at enterprise scale, ideally in trading or similarly data-intensive domains Strong written and verbal communication skills Comfortable with ...

documenting reliable and scalable data science products in complex environments, ideally Energy, Oil & Gas or Commodities Applied knowledge of data science tools (LLMs/RAG etc.) and approaches across all data lifecycle stages. Python or Java and SQL Thorough understanding of underlying mathematical foundations of statistics and machine learning. ...

designing, planning, prototyping, productionizing, maintaining, and documenting reliable and scalable data science products in complex environments. Applied knowledge of data science tools (LLMs/RAG etc.) and approaches across all data lifecycle stages. Advanced SQL knowledge. Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining ...

through to production. Work with messy, large-scale structured and unstructured data to build models that move real business metrics. Lead the design of RAG-style architectures (embeddings, dense search) and advanced NLP/NLU applications. Partner closely with pre-sales and delivery teams to scope opportunities and shape solution ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

React.js + Node.js 100% Remote (UK-based only) 💡 Desirable Skills Knowledge of SQL or React Experience with AI/LLMs or RAG (Retrieval-Augmented Generation) Familiarity with integration testing Exposure to multiple programming languages beyond TypeScript Daily use of AI coding assistants Strong problem ...

environments. Deep understanding of AI governance, ethics, guardrails, compliance , and data privacy. Experience building or deploying LLM-powered systems , agentic workflows, and code-generation pipelines. Strong capability in code review, automated testing, and maintaining quality across AI-assisted codebases. Exceptional communication and stakeholder … engagement abilities—comfortable presenting to leadership. Ability to manage multiple initiatives with attention to detail and strategic alignment. Nice-to-Have Skills Exposure to RAG frameworks, vector databases, embeddings, and graph/temporal data systems. Familiarity with cloud-based deployment (AWS/Azure), containerization, and observability tooling. Experience with prompt ...

powered Predictive Intelligence Platform for corporates and financial institutions. Their technology connects market events, client data, and emerging opportunities through advanced agentic AI and RAG-based systems, helping financial institutions anticipate client needs before they arise. They have built a live MVP in record time, with enterprise client demos underway … lead the design and productionisation of the company’s core AI systems. You will architect, implement, evaluate, and scale RAG pipelines, agentic workflows, and LLM-based intelligence frameworks, driving real-world impact across financial markets. The role is approximately 80% hands-on and 20% strategic, covering Python engineering, system architecture ...

controls • Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) • Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also Had Experience In Some Of These, But If Not We’ll Help You With Them • Experience with … 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) • Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) • Familiarity with Infrastructure as Code (Terraform, CloudFormation) • Experience with data processing frameworks (Spark, Dask ...

precision of AI engineering with the ambition of a fintech disruptor. That’s what this role offers. I’m working with a next-generation technology company that’s fusing agentic AI with financial innovation to create intelligent systems that don’t just automate - they think, adapt, and transform … experience building GenAI systems in production environments. Strong Python skills and a GitHub portfolio showcasing MLE or GenAI projects. Expertise in LLMs, prompt engineering, RAG, vector databases, and agentic frameworks (LangChain, LlamaIndex, DSPy, etc.). Ability to break down complex business domains into computational workflows. Excellent communication skills and comfort ...