AI Engineer
Definition
An AI Engineer is a professional who builds production AI applications by integrating large language models, designing RAG systems, implementing AI agents, and deploying AI-powered features into real products.
Why It Matters
AI Engineering has emerged as one of the fastest-growing tech careers. Unlike traditional ML Engineers who train models from scratch, AI Engineers focus on the application layer - taking existing foundation models (GPT-4, Claude, Llama) and building products with them. This makes the role more accessible to software engineers while still commanding premium salaries.
How It Works
AI Engineers spend their time on: prompt engineering and optimization, building RAG systems for knowledge retrieval, implementing AI agents and workflows, integrating LLMs into existing applications, setting up evaluation and monitoring systems, and managing the full lifecycle of AI features. The work is closer to software engineering than data science.
Career Path
Most AI Engineers transition from software engineering, backend development, or data engineering backgrounds. Key skills include: Python proficiency, API integration experience, understanding of LLM fundamentals, RAG implementation, and production deployment. The role doesn’t require a PhD or deep ML research experience, making it accessible to many developers.