Skills You NEED for AI Engineering in 2026
In this Hindi talk, the speaker outlines the essential skill set for aspiring AI engineers in 2026. She emphasizes that a solid programming foundation is the first requirement, followed by an understanding of how machine learning (ML) and deep learning (DL) differ and how to build models. The discussion moves to foundation models and large language models (LLMs), covering their architecture, generative capabilities, and practical usage. She highlights the importance of vector databases for retrieval‑augmented workflows, and stresses that data engineering knowledge—especially building pipelines that feed data into models—is crucial. The speaker then covers model deployment and optimization, including production‑level considerations and monitoring. Cloud competence (AWS, etc.) is presented as necessary for scaling and managing AI services. Finally, she talks about creating AI agents, applying MLOps principles, and interacting with OpenAI‑style APIs to automate and operationalize AI solutions.
