26 to 44 of 44 Retrieval-Augmented Generation Jobs in the City of London

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 ...

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. ...

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 ...

technology transformation, product leadership or innovation, supported by hands-on delivery experience. Experience with generative and agentic AI, machine learning, predictive analytics, retrieval-augmented generation and enterprise knowledge systems. Knowledge of data architecture and readiness, cloud AI platforms, enterprise integration patterns, AI governance, security ...

production LLM systems that deliver accurate, valuable outcomes for real users. You’ll be responsible for: Building and improving production LLM-driven systems , including RAG and agentic workflows. Developing high-quality, reliable and well-tested Python code. Designing and implementing evaluations (evals) that genuinely measure whether AI systems are improving. … ideally have: 4+ years' experience building production software. 2+ years' experience building production LLM applications. Strong hands-on experience with Python . Experience building RAG systems , LLM applications and/or AI agents. A strong understanding of how LLM systems work, including areas such as embeddings, prompting and model parameters ...

Senior Software Engineer to join a growing AI team and take ownership of the application and integration layer behind a new generation of AI-powered products. This is a genuinely full-stack engineering role, combining production-grade backend development, API design, AI integrations and frontend engineering. … securely and reliably. Experience working closely with designers to deliver production-quality frontend applications. A good understanding of accessibility and frontend performance. Experience with RAG, AI agents, tool use or other generative AI application patterns would be advantageous, although deep ML expertise isn't required. This is an opportunity ...

real client data during Assess engagements - the prototype is the discovery tool, built while the value case is made * Delivering client POCs and MVPs: RAG pipelines, agent architectures, LLM integrations and protocol-driven tooling (MCP, tool orchestration) * Iterating in short loops: demoing every few days, taking feedback, changing course without … front-end, back-end and data engineering to build the whole thing yourself * Hands-on production LLM and agent experience: prompt engineering, agent workflows, RAG, tool orchestration and MCP - with evidence you've shipped AI users actually rely on, and how you proved it could be trusted * Evaluation-driven habits ...

real client data during Assess engagements, the prototype is the discovery tool, built while the value case is made Delivering client POCs and MVPs: RAG pipelines, agent architectures, LLM integrations and protocol-driven tooling (MCP, tool orchestration) Iterating in short loops: demoing every few days, taking feedback, changing course without … front-end, back-end and data engineering to build the whole thing yourself Hands-on production LLM and agent experience: prompt engineering, agent workflows, RAG, tool orchestration and MCP, with evidence you've shipped AI users actually rely on, and how you proved it could be trusted Evaluation-driven habits ...

practical AI architectures and technical solutions Owning solution design from initial requirements through to delivery Architecting agentic AI systems using model APIs, orchestration frameworks, RAG and retrieval patterns Making informed decisions between different models, platforms, low-code solutions and custom development Designing integrations, APIs, data pipelines … Engineering or technical consulting backgrounds. You'll ideally bring strong experience across several of the following: AI/LLM solution architecture Agentic AI systems RAG and retrieval architectures Model APIs and orchestration frameworks Microsoft Copilot Studio Power Platform/Power Automate/Dataverse Azure and Microsoft 365 Python ...

opportunity to influence the technical direction of a newly formed AI Lab. Key Responsibilities • Build and deploy production-grade LLM systems • Design and optimise RAG and retrieval workflows • Fine-tune models for tone, style, and output quality • Develop audio-first AI products using TTS/STT workflows • Build … greenfield environment Key Details • Salary: Up to ~£120k base • Working model: Hybrid (3+ days/week in London) • Stack: Python, HuggingFace, LangChain, RAG, multimodal AI, TTS/STT, evaluation frameworks • Sponsorship: To be confirmed Interested? Please apply below. ...