51 to 60 of 60 Retrieval-Augmented Generation Jobs in Central London

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 ...

ship customer-facing applications, APIs and internal platforms. Remain hands-on with coding, testing, architecture and code reviews. Build AI-enabled products using LLMs, RAG, agents and model APIs. Take AI ideas from rapid prototypes through to reliable production systems. Work across Python, React/TypeScript, Django, FastAPI, PostgreSQL … scalability, security, reliability and maintainability. Technology Python | React | TypeScript | Django | FastAPI | PostgreSQL | AWS | Docker | REST APIs | CI/CD | Git AI experience across LLMs, RAG, agentic workflows, embeddings, prompt design or model evaluation is particularly valuable. What Theyre Looking For 510 years' commercial software engineering experience. Strong, recent hands-onPython ...

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 applications … chatbot capabilities. Build and improve RAG pipelines, retrieval and document search. Extend LlamaIndex agents, workflows, retrievers and tool-calling capabilities. Integrate LLMs, APIs, databases and structured organisational data. Improve AI answer quality, citations, performance, security and reliability. Deliver well-tested, documented code and support technical handover. Key Requirement ...

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 applications … chatbot capabilities. Build and improve RAG pipelines, retrieval and document search. Extend LlamaIndex agents, workflows, retrievers and tool-calling capabilities. Integrate LLMs, APIs, databases and structured organisational data. Improve AI answer quality, citations, performance, security and reliability. Deliver well-tested, documented code and support technical handover. Key Requirement ...

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. ...