10 of 10 Contract Retrieval-Augmented Generation Jobs in London

features-from data ingestion and feature engineering to model training, evaluation, and deployment Develop LLM/GenAI solutions (prompt engineering, tool use, guardrails) and RAG pipelines (chunking, embeddings, vector search, caching, re ranking) Optimise training and inference performance via batching, quantisation, distillation, LoRA/PEFT, accelerator utilisation (GPU/… building GenAI applications using Python Hands-on Experience with API Development and Microservices architecture and End to End integrations Knowledge of RAG (Retrieval-Augmented Generation) and ADK, MCP Solid understanding of LLMs, prompt engineering, and graph-based workflows Hands-on Experience with API Development ...

develop GenAI applications for Code Translation, Text Extraction, Summarisation and SDLC Optimization etc. Hands-on Experience with AI Agents, Chat bots, RAG (Retrieval-Augmented Generation), and vector databases (PG vector/croma DB) Hands-on Experience with GenAI Performance Evaluation tools like Pegasus, Ragas ...

Weaviate, Chroma) Cloud (AWS/Azure/GCP) Docker, Kubernetes CI/CD, observability, testing for AI systems Experience Strong experience building LLM applications, RAG systems, or AI agents Understanding of prompt engineering, tool-calling, and orchestration frameworks Ability to work autonomously in a scale-up environment A product-focused ...

quality metrics: task success rate, groundedness, containment, FCR Experience on Google Cloud Platform (preferred) or equivalent hyperscale Deep understanding of LLMs, generative AI, RAG patterns, vector databases, embeddings, and prompt/guardrail engineering Desirable Skills/Knowledge/Experience Knowledge of MLOps/AgentOps, CI/CD, and observability Strong ...

business logic * Experience in small, fast-moving teams (startup, scaleup, or consulting) * Strong communication and documentation skills Nice to have: * Experience with LLM workflows (RAG, LangChain, etc.) * Experience in logistics, trade, or compliance data * Experience supporting client-facing or pre-sales conversations To Apply: Please email ...

systems (LangChain/LangGraph or similar) into production Hands-on experience with AI agents, agentic workflows, and multi-step reasoning Experience designing and implementing RAG systems with real-world impact Familiarity with MCP or similar orchestration patterns (FastMCP/FastAPI) Understanding of LLM limitations and trade-offs (hallucination, latency, cost ...

architectures Design end-to-end architectures using Azure OpenAI, Azure AI Search, ML, data platforms, compute, networking, and identity Select and define architecture patterns (RAG, agentic workflows, streaming vs batch, hybrid approaches) Define non-functional requirements: security, scalability, performance, cost, availability Ensure alignment with Azure best practices, security standards, compliance ...

Experience working with LLM APIs and prompt engineering Great to have Additional exposure to data platforms such as Databricks or ThoughtSpot Understanding of RAG pipelines and vector databases (Hands-on experience across several of the above systemsis beneficial) Commercial & Operational Experience operating in a SaaS environment with a strong understanding ...

systems (SharePoint, Dataverse, SQL, and REST APIs). GenAI Configuration: Implement and fine-tune Generative AI features, including 'boosted conversations' and knowledge-base grounding (RAG). Governance & Security: Ensure all solutions adhere to strict SC-cleared environment protocols, focusing on data residency and responsible AI principles. Stakeholder Collaboration: Work with ...

Work closely with stakeholders - listening, probing, and shaping solutions around real needs. Essential Experience Experience automating human-centric processes (approvals, performance workflows, document generation, analytics, etc.). Proven experience building AI agents and multi-step automation flows. Strong hands-on engineering skills (clean, explainable, well-structured code). … Expertise using ChatGPT Enterprise for workflow automation. Skilled in designing prompts, guardrails, and evaluation logic for reliable outputs. Experience building retrieval pipelines (RAG), vector search, or context-aware systems. Comfortable integrating AI systems with APIs and internal platforms. How to Apply If you're an AI Engineer ...