26 to 50 of 60 Retrieval-Augmented Generation Jobs in Central London

research and make investment decisions. Working closely with Portfolio Managers, Research Analysts, Sustainability teams, Architects and Engineers, you will define and deliver next-generation capabilities leveraging Generative AI, agentic workflows and advanced analytics to create measurable business value across global investment teams. Key Responsibilities Own the vision, roadmap … investment data, holdings, benchmarks and fund look-through capabilities. Experience delivering AI-powered solutions, including Large Language Models (LLMs), Retrieval Augmented Generation (RAG), AI assistants, agentic workflows and knowledge discovery platforms. Demonstrated product management experience, including product strategy, roadmap development, prioritisation, backlog management ...

experience Strong React.js, Node.js and TypeScript experience Next.js and RESTful APIs GCP including Cloud Run Kubernetes and Terraform AI/LLM integrations, AI agents, RAG or agentic workflows Unit, integration and end-to-end testing CI/CD, secure coding and DevSecOps Experience building scalable, high-traffic applications Strong ...

Fargate or similar orchestration technologies * NoSQL and relational databases * Messaging and integration services * Cloud storage solutions - Practical experience applying AI technologies such as LLMs, RAG, AI agents and automation within software solutions. In accordance with the Employment Agencies and Employment Businesses Regulations 2003, this position is advertised based upon ...

work forward independently. What makes you stand out? Experience building AI/LLM-enabled products in production or controlled enterprise environments (e.g. agentic workflows, RAG, prompt engineering, evaluation and governance patterns) Experience with React/Next.js and modern web tooling. Familiarity with document/NoSQL stores (e.g. MongoDB) and data ...

code You have experience working with large-scale, unstructured text data and LLMs — including prompt design, evaluation (e.g., golden sets, LLM‐as‐judge), and RAG patterns You have demonstrated ability to mentor junior data scientists, balance speed, risk, and analytical rigor You have experience with advanced visualization techniques/best ...

concept work. Reviewing code and technical outputs to maintain high engineering and quality standards. Designing and delivering Generative AI and LLM solutions , including RAG architectures, prompt engineering, vector search and integration with Azure AI services. Defining engineering approaches for LLM applications, agentic AI systems, machine learning solutions and AI platforms … TensorFlow . Practical experience with Databricks , including MLflow and Spark-based data processing. Hands-on knowledge of Generative AI and LLMs , including prompt engineering, RAG architectures and vector search. Strong understanding of MLOps , including CI/CD, model testing, deployment, monitoring and model lifecycle management. Cloud experience, ideally within ...

/GCP). Ability to standardise and influence across teams. Nice to Have Lakeflow connectors, RBAC/masking, GenAI (Mosaic AI, Vector Search, RAG), Lakebase. #J-18808-Ljbffr ...

launch and architecting AI systems on cloud platforms (e.g., GCP). Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience leading technical discovery sessions with customers. Active, or the ability to obtain, a Security Check ...

such as Microsoft, Oracle, or similar platforms.Background in change management, organizational design, or enterprise transformationExperience with AI/ML concepts beyond LLMs, including NLP, RAG architectures, and model evaluation frameworksA get-things-done mindset with strong bias for action — comfortable operating in unstructured fast moving environmentsUnleash Your PotentialWhen you join ...

experience driving cloud/AI transformation within Insurance, Financial Services, or similarly highly regulated industries. Technical Acumen: A strong architectural understanding of GenAI concepts (RAG, AI Agents, Agentic Workflows) and DevSecOps automation. Delivery Mastery: Expertise in benefits management, project planning, and crisis mitigation for large-scale enterprise deployments. To Apply ...

experience driving cloud/AI transformation within Insurance, Financial Services, or similarly highly regulated industries. Technical Acumen: A strong architectural understanding of GenAI concepts (RAG, AI Agents, Agentic Workflows) and DevSecOps automation. Delivery Mastery: Expertise in benefits management, project planning, and crisis mitigation for large-scale enterprise deployments. To Apply ...

outcomes. Even better... Experience building or deploying AI/LLM agents in production hands-on with the tools behind them (eval frameworks, agent tooling, RAG, prompt engineering) working closely with technical counterparts. You've been a founder, founding team member, or operator you know how to balance craft, ownership ...

need of a Python engineer to support a customer with building an AI Chatbot using Python and LlamaIndex. Key Technologies: Python 3.12+ LlamaIndex/RAG Azure AI Foundry/OpenAI Typesense/Vector Search PostgreSQL/Pydantic Plotly Dash Key Duties: Develop and enhance production-grade Python AI appli click ...

Proven experience engineering technology solutions in complex environments and supporting production operations Applied AI/ML and GenAI experience with knowledge of established patterns (RAG, tool use, guardrails, evaluation, agents) and an ability to evaluate tools and approaches Experience of working in teams employing agile practices and using modern SDLC ...

coding tools (Claude Code, Devin, Cursor/Windsurf, Copilot) with informed views on where each earns its keep. LLM application engineering — agent orchestration, RAG, structured outputs, evals. Prior consultancy or client-facing delivery experience. Cloud and data infrastructure depth (GCP/AWS, Terraform, CI/CD, warehouses, ETL). Front ...

doesn't make sense, and delivering in short, time-boxed cycles where validated outcomes matter more than perfect solutions. Agentic AI/LLMs: Building RAG pipelines, tool-augmented agents and agentic workflows; familiar with prompt engineering, context management, evaluation and observability. Agent fundamentals: Understands how agents use memory … information to universities. We help innovators turn knowledge into new products. We help health professionals improve patient care and educators train the next generation of doctors and nurses. Connecting quality content and innovative technologies, we make progress go further and happen faster. And by championing inclusion and sustainability ...

years of experience managing large tech, cloud, or consulting projects. Mandatory Tech Skills: Real, hands-on experience with AWS AI services-specifically Amazon Bedrock (RAG, prompt engineering) and AgentCore . Service Management: A strong background in SIAM and ITSM frameworks. Leadership: proven ability to comfortably talk tech with developers ...

efficiency ; shorter cycle times, less manual effort, higher accuracy, lower cost-to-serve. Engineer the agent core: apply prompt engineering, context engineering, prompt caching, RAG/context-graph retrieval, memory, tool/function calling, MCP integration and multi-agent orchestration. Integrate to standards: connect agents into client ecosystems … Agents SDK, AWS Bedrock AgentCore or Microsoft Agent Framework/Semantic Kernel). Solid command of agent engineering: prompt engineering, context engineering, prompt caching, RAG/context graphs, tool/function calling, MCP, and multi-agent orchestration. Eval-driven development: designing evaluation harnesses and measuring agent quality, safety and reliability. ...

event-driven architectures, including Kafka Agentic AI and ML Commercial and open-source LLMs integrated into agentic workflows Tooling for agent orchestration, retrieval-augmented generation, vector storage, and evaluation Strong schema, validation, and state management practices AI-assisted developmen t Fluency with AI-assisted ...

Kubernetes, and cloud-native infrastructure. Design and deploy scalable batch and real-time ML pipelines supporting customer-facing applications. Develop and operationalise LLM applications, RAG systems, and Generative AI capabilities for content understanding, summarisation, classification, and recommendation use cases. Build evaluation frameworks and observability solutions to monitor model quality, reliability … Intelligence, Statistics, Data Science, or a related STEM field. Experience applying Generative AI and LLMs to customer-facing products and designing, building, or scaling RAG systems. Experience in search, ranking, recommendations, personalisation, content intelligence, moderation, NLP, computer vision, or related AI domains. Experience with Airflow or comparable workflow orchestration platforms. ...

systems. Strong technical understanding of AI/ML and generative AI systems, including model development, model evaluation, data pipelines, embeddings, retrieval-augmented generation, prompt engineering, monitoring, drift, robustness, explainability, and safety testing. Demonstrated ability to assess technical AI risks and recommend practical controls ...

closely with engineers to translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search). Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies, including hybrid search (semantic … Strong experience designing and running experiments, including model evaluation and iteration. Strong coding skills in Python. Experience with generative AI techniques (e.g., prompt engineering, RAG). Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases. Experience designing agentic workflows and reasoning strategies, with hands ...

closely with engineers to translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search). Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies, including hybrid search (semantic … Strong experience designing and running experiments, including model evaluation and iteration. Strong coding skills in Python. Experience with generative AI techniques (e.g., prompt engineering, RAG). Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases. Experience designing agentic workflows and reasoning strategies, with hands ...

plane for staff and customer authentication. Contribute to AI-enabled quotation and knowledge tools, including human-in-the-loop quote drafting and retrieval-augmented knowledge features. Collaborate closely with mobile, product and engineering colleagues where your APIs are consumed across different surfaces. Take part in architecture … through to delivery. Useful Additional Experience Exposure to React or React Native, particularly where APIs support web or mobile products. Experience with retrieval-augmented generation, vector search or integrating LLM-based features into production products. Experience working in a scale-up, transformation programme ...

plane for staff and customer authentication. Contribute to AI-enabled quotation and knowledge tools, including human-in-the-loop quote drafting and retrieval-augmented knowledge features. Collaborate closely with mobile, product and engineering colleagues where your APIs are consumed across different surfaces. Take part in architecture … through to delivery. Useful Additional Experience Exposure to React or React Native, particularly where APIs support web or mobile products. Experience with retrieval-augmented generation, vector search or integrating LLM-based features into production products. Experience working in a scale-up, transformation programme ...