This roadmap gives you a clear, month-by-month plan to become a ai engineer from Lucknow in 2026. Each step includes what to learn, which tools to use, and what project to build — so you know exactly where you stand at every stage.
The Step-by-Step Roadmap
Python & API Foundations
2 monthsPython basics, async programming, HTTP APIs, JSON handling, git — the engineering foundation.
Tools: Python 3.11+, VS Code, Git, Postman
💡 Build a simple REST API with FastAPI early. It teaches you how real AI apps are structured.
LLM APIs & Prompt Engineering
1–2 monthsOpenAI/Claude/Gemini API integration, system prompts, token management, chain-of-thought, tool calling.
Tools: OpenAI / Claude / Gemini API, Python requests
💡 Build a chatbot CLI that maintains conversation history. Then build a document summariser with streaming output.
RAG — Retrieval Augmented Generation
1.5 monthsEmbeddings, vector databases, chunking strategies, retrieval pipelines, RAG evaluation.
Tools: Pinecone / Chroma, LangChain / LlamaIndex, FastAPI
💡 Build a RAG document Q&A app over your own PDFs. This is the #1 project Lucknow AI employers ask about in 2026.
AI Agents & Tool Use
1.5 monthsAgent loops, tool calling, memory systems, multi-agent workflows, automation agents.
Tools: LangChain / LangGraph, AutoGen basics, Python
💡 Build an AI agent that can search the web + do calculations. Multi-agent workflows are the biggest trend in 2026.
Deployment & MLOps
1–2 monthsFastAPI, Docker, cloud deployment (AWS/Azure basics), CI/CD, monitoring.
Tools: Docker, FastAPI, AWS / Azure basics, GitHub Actions
💡 Deploy your RAG app on Render/Railway. A deployed AI project is worth 10x a local-only project on your resume.
Portfolio & Job Prep
1 monthGitHub portfolio polish, project write-ups, AI-specific interview prep, resume.
Tools: GitHub, LinkedIn, Interview platforms
💡 DSWallah placement support covers all of this — resume review, mock interviews, referrals to Lucknow and remote roles.