What is AI engineer?AI engineer kya hai?

🧸 Think of it likeAise samjho

Like an electrician who doesn't make the power plant (the AI model) but wires it safely into your house so the lights and fans actually work.Ek electrician jaisa jo power plant (AI model) nahi banata, par use aapke ghar mein safely jodta hai taaki lights aur pankhe sach mein chalein.

📘 ExplainedVistaar se

AI engineers usually don't train big models from scratch. They connect models to real data and apps: prompts, RAG, tool calling, agents, evaluation, guardrails, latency and cost. Strong software engineering matters more than heavy maths. Related roles include ML engineer (trains and serves models), MLOps engineer (runs them reliably) and AI product engineer (ships user facing AI features).AI engineers aam taur pe bade models shuru se train nahi karte. Woh models ko asli data aur apps se jodte hain: prompts, RAG, tool calling, agents, evaluation, guardrails, latency aur cost. Bhaari maths se zyaada mazboot software engineering zaroori hai. Jude roles: ML engineer (models train aur serve karta hai), MLOps engineer (unhe reliably chalata hai) aur AI product engineer (users ke liye AI features ship karta hai).

💡 Real exampleAsli example

Building a company chatbot that answers from HR policies with citations is typical AI engineer work.HR policies se citations ke saath jawaab dene wala company chatbot banana typical AI engineer ka kaam hai.

📖 Learn it step by stepStep by step seekho

• Landing the AI role: resume, applications and interviewsAI role paana: resume, applications aur interviews
• Calling an LLM API: keys, requests and costsLLM API call karna: keys, requests aur costs

🔗 Related termsJude hue shabd

• RAGLetting an LLM answer from your documents: search for relevant passages first, then generate an answer from them with citations.LLM ko aapke documents se jawaab dene dena: pehle relevant hisse dhoondho, phir unhi se citations ke saath jawaab banao.
• AgentAn LLM that works in a loop: plans a step, uses a tool, looks at the result, and decides the next step until the goal is done.Ek LLM jo loop mein kaam karta hai: step plan karta hai, tool use karta hai, result dekhta hai, aur goal poora hone tak agla step tay karta hai.
• MLOpsThe practices and tools for putting ML models into production and keeping them healthy.ML models ko production mein laane aur swasth rakhne ke tarike aur tools.