Generative AI Engineer

Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI-centric libraries such as TensorFlow and PyTorch. • Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources. • Design, develop, and deploy AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models. • Implement and manipulate complex algorithms essential for developing and optimizing generative AI models. • Manage data pipelines involving data pre-processing, augmentation, and synthetic data generation to enhance model training and performance. • Ensure robust data handling practices including cleaning, labeling, and structuring datasets for generative AI workflows.