• Develop AI Models: Design and implement machine learning models and algorithms to solve specific business challenges. • Build GenAI Applications: Architect applications using LLMs (OpenAI, Llama 2, Anthropic) and RAG (Retrieval-Augmented Generation) pipelines. • Fine-Tuning: Fine-tune pre-trained models on proprietary datasets to improve performance and domain accuracy. • Model Deployment: Deploy and scale AI models into production environments using MLOps best practices (Docker, Kubernetes). • Data Engineering: Collaborate with data teams to clean, preprocess, and manage large datasets for model training. • Stay Cutting-Edge: Continuously research and integrate the latest advancements in AI/ML (e.g., Agents, Vector Databases) into our product stack.