Strong conceptual understanding of Generative AI systems, including Large Language Models (LLMs), transformers, and foundation models across text, image, and multimodal data.
Proficiency in extracting insights and generating intelligent outputs from structured, semi-structured, and unstructured data using advanced Generative AI techniques.
Expertise in prompt engineering, prompt optimization, and fine-tuning strategies to maximize the performance and reliability of generative models.
Hands-on capability to build and deploy LLM-powered applications, including chatbots, copilots, knowledge assistants, and AI-driven automation tools.
In-depth understanding of Retrieval-Augmented Generation (RAG) and the integration of vector databases for scalable and context-aware AI systems..
Ability to design autonomous AI agents capable of reasoning, decision-making, tool usage, and multi-step workflow execution.
Strong knowledge of AI ethics, governance, and responsible AI practices, ensuring safe, compliant, and explainable AI solutions.
Practical experience in deploying, monitoring, and optimizing Generative AI models using cloud platforms and MLOps best practices.
Confidence to work with enterprise-scale Generative AI use cases, including content generation, document intelligence, conversational AI, and business process automation.
A portfolio of real-world Generative AI projects and a capstone solution, demonstrating job-ready skills aligned with current industry demands.