AI Engineer Capstone and Interview Preparation
Learn to prove your AI engineering skills: three portfolio projects for RAG, agents, and a deployed service, plus system design and interview prep.
What You'll Learn
Understanding What AI Engineer Interviews Test
A hiring panel in Pune watches a twelve-minute demo. The candidate's RAG chatbot answers three questions beautifully.
Building Project 1: Production RAG Chatbot
Project 1 is acme-assist's help-centre chatbot, rebuilt as a repository a stranger can clone, run, and judge. The goal is not a clever demo.
Building Project 2: Reliable AI Agent
Project 2 is acme-assist's refund agent: a single agent that handles a realistic multi-step task, and, more importantly, stops correctly when it...
Deploying Project 3: The AI Service
Project 3 takes Project 1 or Project 2 and wraps it as a real service that other people can call.
Choosing Optional Projects: Multi-Agent System and Fine-Tuned Model
The two optional projects are for learners who want to go deeper, and they only help if they teach you something honest.
Presenting Your Work to a Hiring Manager
Presentation is part of the engineering. A reviewer opens your repository for about two minutes, so the README, the evidence tables, and the diagram...
Skills You'll Master
Curriculum Index9 topics
Understanding What AI Engineer Interviews Test
A hiring panel in Pune watches a twelve-minute demo. The candidate's RAG chatbot answers three questions beautifully.
Building Project 1: Production RAG Chatbot
Project 1 is acme-assist's help-centre chatbot, rebuilt as a repository a stranger can clone, run, and judge.
Building Project 2: Reliable AI Agent
Project 2 is acme-assist's refund agent: a single agent that handles a realistic multi-step task, and, more...
Deploying Project 3: The AI Service
Project 3 takes Project 1 or Project 2 and wraps it as a real service that other people can call.
Choosing Optional Projects: Multi-Agent System and Fine-Tuned Model
The two optional projects are for learners who want to go deeper, and they only help if they teach you something honest.
Presenting Your Work to a Hiring Manager
Presentation is part of the engineering. A reviewer opens your repository for about two minutes, so the README, the...
Walking Through Three AI System Design Questions
In the system design round, you get a vague prompt and a whiteboard, and the interviewer watches how you think.
Practising the Python, SQL, and ML Screens
The screens reward steady practice more than cleverness.
Checking You Are Job-Ready
You are job-ready when your evidence is in public, your explanations are rehearsed, and your practice problems pass...
Career Impact
Roles that use the skills in this module.
AI Engineer
MLOps Engineer
Platform Engineer
Next Modules
Practice on the Coding Sheet
Not a software engineer sheet. Every problem comes from real DevOps, SRE, Platform and Cloud interviews, from your first script to a system you build yourself.
Open the Coding SheetFrequently Asked Questions
Three finished projects beat ten half-finished ones. A good set is a production RAG chatbot, a reliable AI agent, and one of them deployed as a real service. Each one needs an evaluation result, safety notes, and a README that explains your decisions.
Rarely. A notebook that ran once proves the idea can work, not that the system works. Hiring managers look for a running service, an evaluation set with numbers, and written safety considerations.
Many do. Plan for arrays, strings, and hashmaps at easy to medium level, alongside Python and SQL screens. Treat it as a short daily habit, not a separate course.
For Project 3, yes: the point is a live link and real traces, cache numbers, and costs. Keep it small, set a spending alert, and tear it down when you are done. Projects 1 and 2 can run locally.
Ranges vary widely with company type, skill, location, and negotiation, so treat any figure as illustrative, not a promise. This module lists rough bands by experience level. Product companies and AI-first startups usually sit at the top of each band.