The position involves the ideation, development, and deployment of AI/ML solutions with a focus on various applications such as prediction, recommendation, text analytics, computer vision, natural language processing (NLP), and content intelligence. The role requires rapid prototyping and the creation of proof of concepts (PoCs) in areas including large language models (LLMs), deep learning (DL), and machine learning (ML). Additionally, the candidate will be responsible for fine-tuning and deploying distributed OpenAI models, applying prompt-engineering techniques to optimize performance for specific use cases. The development of applications using Retrieval-Augmented Generation (RAG) techniques and agentic workflows is also a key responsibility, enhancing AI solutions with advanced information retrieval and vector databases. Collaboration with cross-functional teams is essential to ensure that AI solutions align with client needs and project goals. The candidate will need to stay informed about the latest advancements in generative AI, machine learning, and cloud services to continuously optimize the technical stack. Effective technical communication is crucial, as the candidate will need to convey complex concepts to non-technical audiences and provide training sessions to enhance data science skills within the organization. Knowledge of containerization and deployment processes is required to ensure scalable and efficient AI solutions, as well as the integration of Azure OpenAI and other AI services into enterprise applications.