for text-heavy datasets. Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-AugmentedGeneration (RAG). Experience in anomaly detection techniques, algorithms, and applications. Excellent problem-solving, communication (verbal and written), and teamwork skills. Preferred qualifications, capabilities, and skills Experience More ❯
for intelligent data discovery, extraction, and decision-making. Oversee the integration of LLMs, knowledge graphs, retrieval-augmentedgeneration (RAG), and reinforcement learning for autonomous task execution. Champion the application of explainable and trustworthy AI principles in all solutions. Hands-on Technical Leadership Serve as … leadership responsibility (people management experience not required). Deep expertise in building intelligent systems with one or more of the following: LLMs, agent frameworks, RAG, knowledge representation, or autonomous data pipelines. Strong programming and software engineering skills (Python preferred; familiarity with cloud-native and MLOps tools). Demonstrated experience in More ❯
Glasgow, Renfrewshire, United Kingdom Hybrid / WFH Options
Capgemini
unstructured data sources. Experimenting with the integration and fine-tuning of models with Vector databases and embeddings to support semantic search, RAG (retrieval-augmentedgeneration), and domain-specific applications. Working within a Data Mesh architecture, collaborating across domains to ensure scalable, interoperable data products More ❯