Career path

Full-Stack Applied AI Engineer

You become the person who turns an idea into a live AI product by Friday.

Most AI 'experts' can run a model in a notebook. You'll be one of the few who can put it in front of a million people: the screen they tap, the API behind it, the database that remembers them, and the AI that makes it feel like magic. Startups hire this person first.

TypeScriptReactNext.jsPostgrespgvectorAI SDKLLM APIsVercel
A day in your future life
10:00

Stand-up. The founder wants 'chat with your invoices' live for a customer demo on Thursday.

10:30

You write a one-page spec, sketch the data flow and split it into 5 slices for your coding agent.

13:00

The agent has built the upload flow. You review the diff and catch a bug where one user could read another user's files.

15:30

You run your eval set: 41 of 50 answers correct. You change the chunking strategy and it goes to 47.

18:00

Deployed. The founder sends a screenshot from a customer: 'this is insane'.

What you'll build

  • AI copilots inside real products
  • Chat over company documents (RAG)
  • Agents that take actions through tools
  • The full app around the AI: auth, payments, dashboards

Your maths edge

Embeddings are vectors and similarity is a dot product. Evals are statistics. Ranking, sampling (temperature, top-p) and cost/latency trade-offs are all applied maths. You'll understand why things work while others copy settings from blog posts.

Demand

Fastest-growing title for new grads (LinkedIn's 'AI engineer' has topped Jobs on the Rise two years running). Startups and product companies want builders who ship.

Entry pay (India, rough)

Roughly ₹6–15 LPA in India at startups and product companies; more at top product firms. Wide range, driven by portfolio.

The honest truth

Plain 'junior developer' roles are shrinking because AI writes boilerplate. Juniors who can ship AI features end to end are the ones getting hired. Your portfolio matters more than your college name here.

2-minute taste test

Try a few minutes of the job

Three real situations from a Full-Stack AI engineer's week. Pick what you'd do and see how a senior would think about it. There's no score and no right path for you. It's just a feel for the work.

Situation 1 of 3

Your 'chat with PDFs' feature sometimes invents answers that aren't in the document. A customer complained. What do you do first?

The roadmap

From your first line of code to people using what you built

Tick off steps as you go. Finishing a quest reveals a sealed insight, and finishing a stage unlocks a capability. Everything is saved in this browser.

Before you start: where to use AI (and where not to)

Use AI freely for

  • Explaining a concept, an error message or someone else's code, then asking follow-up 'why' questions
  • Quizzing you: 'ask me 5 questions on what I just learned'
  • Reviewing code you wrote: bugs, edge cases, security holes

Use carefully

  • Writing code for a concept you're learning: write it yourself first, then compare with the AI's version
  • Choosing libraries: AI may suggest outdated packages, so check the docs and the last release date
  • Facts and numbers: verify anything you'll put in a README, resume or memo

Don't use AI for

  • Code you can't explain line by line. If you can't explain it, you don't own it, and interviews will show it
  • Skipping the struggle. The 20 minutes you spend stuck is when learning happens
  • Deciding what to build or what your analysis concludes. That judgement is your job
Type the first version yourself. Delegate the second. Review every one.

Every quest has its own "use AI for / avoid" note. The full guide is in the AI Playbook.

Remaining work
~243h
At this pace
17 weeks
20 quests

Sprint Zero

Five days, no more. You already know how to program, so this is about learning the shape of the stack, not memorising it. You'll learn the details while building.

5 days4 quests~25 hours
Finish this stage to unlock: You can read a modern TypeScript web stack and put a page on the internet.

Learn by building

Seven small builds, each teaching one real concept by doing it. They stack: by the end, they make up a complete AI product.

~4 weeks8 quests~56 hours
Finish this stage to unlock: You can build, secure and deploy a full-stack AI app end to end.
Job signal: Start applying for internships at startups now. You have something real to show. How to apply →

Company-style builds

Real briefs, the kind a product manager would give you: problem, goal and what 'done' looks like. No step-by-step instructions. Working out the how is the job.

~4 weeks3 quests~72 hours
Finish this stage to unlock: You can take a vague business problem to a working, measured product, the way teams do it.
Job signal: Apply broadly now: internships and full-time roles at startups, product companies and GCCs. How to apply →

Architect mode

You know how the pieces work, so stop typing every line. From here on you design, write the spec, direct AI agents and review their work like a tech lead.

~1.5 weeks2 quests~17 hours
Finish this stage to unlock: You can design a system, break it into slices, direct AI agents to build it and catch their mistakes before users do.

Your meaningful project

One project that real people use beats ten tutorial clones. This becomes the story in every interview.

4–6 weeks3 quests~73 hours
Finish this stage to unlock: You have shipped something people actually use, and you can tell the story of how you built it, measured it and improved it. That's the whole job.
Job signal: This project is your headline. Put it at the top of your resume and LinkedIn and talk about it in every interview. How to apply →
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