use of associated tools and applications to complete these tasks. Ability to travel to client site, where required, will be a consideration. Experience in processing large amounts of structured and unstructured data, including integrating data from multiple sources through ingestion and curation functions on AWS cloud using AWS native … or custom programming. Knowledge of data mining, machine learning, naturallanguageprocessing is an advantage. You enjoy working within cross-functional Agile teams and you are familiar with Scrum ceremonies. Youll be comfortable designing and building for the AWS cloud and will have designed and worked on More ❯
part of our Group's RAG Initiative, you will collaborate with a cross-functional team to implement self-service AI-driven solutions - ranging from NLP Data Analysis and Data Discovery to other analytics assistants we will be deploying to the business to streamline data access, insights retrieval, and business process … SQL, funnels, user journeys exploration, retention, features active users, attribution, data exploration tool etc. Collaborate with data analysts to enable seamless user experiences for naturallanguage queries and structured analytics and data modelling using dbt. Implement query translation and enhancement techniques to improve LLM accuracy and retrieval quality. … ML integration. Strong knowledge of Python, FastAPI, Flask, or Node.js for backend API development. Experience with LLM-based architectures, retrieval-augmented generation (RAG), and NLP techniques. Proficiency in SQL, Redshift, and data warehousing concepts. Experience integrating structured and unstructured data sources for AI-driven applications. Knowledge of dbt, metadata management More ❯
role requires a deep understanding of AI regulations, compliance standards, and security best practices, with a strong focus on Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and secure AI architectures. The ideal candidate will have hands-on experience with LLM security, AI governance frameworks, and regulatory compliance, along … adherence to AI governance and compliance frameworks. Design and implement Retrieval-Augmented Generation (RAG) architectures to optimize information retrieval for LLMs. Work with Large Language Models (LLMs), fine-tuning, deploying, and integrating them into enterprise systems. Ensure LLM security by implementing safeguards against prompt injections, data leaks, and adversarial … developing and deploying AI/ML models. RAG Expertise: Experience in Retrieval-Augmented Generation and related vector databases (e.g., Pinecone, FAISS, Weaviate). LLMs & NLP: Experience working with LLMs (OpenAI, Anthropic, Hugging Face, etc.), including model tuning, security, and optimization. Regulatory Knowledge: Understanding of AI governance, compliance frameworks, and security More ❯
