AI Engineer kit

Artificial Intelligence and Generative AI are rapidly transforming how modern software systems are built. Today, companies expect engineers not only to understand machine learning models but also to design end-to-end AI systems using LLMs, RAG architectures, and AI agents.

Interviews for AI and Generative AI roles now focus on both foundational knowledge and practical system design skills. Candidates are often asked questions about model architectures, retrieval systems, vector databases, prompt design, and increasingly about agent-based AI systems that can reason, use tools, and perform multi-step tasks.

The AI / GenAI Engineer Interview Kit is designed to help you prepare for these modern interviews. This course brings together 500+ structured interview questions and explanations covering the full stack of knowledge required for AI and Generative AI engineering roles.

From core AI fundamentals to modern LLM architectures and agent-based systems, this interview kit helps you build the conceptual clarity needed to confidently handle technical discussions in real industry interviews.

Who This Course Is For

This course is designed for learners preparing for AI and Generative AI engineering interviews, including:

• AI Engineers
• Machine Learning Engineers
• Generative AI Engineers
• LLM Engineers
• AI Agent Developers
• Software Engineers transitioning into AI roles
• Students preparing for AI / ML interviews

It is especially useful for professionals who want to understand how modern AI systems are designed and deployed in production environments, including systems powered by LLMs, RAG pipelines, and AI agents.

What This Course Covers

This interview kit covers the major topics that companies expect candidates to understand when building modern AI and generative AI systems.

AI and Machine Learning Foundations

• Statistics for AI
• Machine Learning fundamentals
• Deep Learning concepts
• Natural Language Processing (NLP)

Modern Generative AI Concepts

• Transformers architecture
• Large Language Models (LLMs)
• Prompt engineering techniques
• Model fine-tuning strategies

Generative AI System Architecture

• Retrieval-Augmented Generation (RAG)
• Vector databases and embeddings
• Memory systems for AI applications
• Caching strategies for LLM systems

AI Agents and Intelligent Workflows

• AI agent architectures
• Tool usage and reasoning loops
• Multi-step agent workflows
• Multi-agent collaboration systems

Building and Deploying AI Applications

• Generative AI system design
• API-based AI architectures
• FastAPI deployment for AI applications
• Production considerations for AI systems

Value You Will Gain From This Course

By completing this course, you will:

• Practice with 500+ AI and Generative AI interview questions
• Strengthen your understanding of AI, ML, and deep learning fundamentals
• Learn how LLM-based systems are designed and built
• Understand the architecture behind RAG systems and vector search
• Gain exposure to AI agent architectures and workflows
• Learn how to design production-ready AI systems
• Improve your ability to explain complex AI concepts during interviews

This interview kit is designed to help you build the knowledge and confidence needed to succeed in interviews for AI Engineer, Machine Learning Engineer, Generative AI Engineer, and AI Agent Developer roles.