AI Engineer
An AI engineer builds products on top of AI models: assistants, agents, search and AI features inside apps.
- Call LLM APIs and design prompts
- Build retrieval (RAG) over a team's data
- Give models tools and evaluate their answers
- Ship AI features safely
- A RAG app over your own documents
- An agent that uses tools
- An evaluation suite for prompts
Where it leads: Senior AI engineer, ML engineer, or AI platform work.
Every skill, at the level the job needs
Updating… · change the level or company to see how it shifts
python
core- Type casting
- Basic Syntax
- Exceptions
- Exception handling
- Basic data types
- Variables
prompt-engineering
core- Introduction to Generative AI and LLMs
- Introduction to LLMs
- Prompt Engineering
- Introduction to Prompt Engineering
- Tokenization
- Context Window
git-github
core- git init
- What is Version Control?
- Why use Version Control?
- git config
- Local vs Global Config
- Git
ai-engineer
core- Impact on Product Development
- Roles and responsibilities in a development team
- Meet the AI engineer
- AI Engineer
- AI vs AGI
- Introduction to Generative AI and LLMs
datastructures-and-algorithms
core- Language Syntax
- Control Structures
- Python
- Pseudocode
- Pseudocode basics
- Functions
What the levels mean
- L1 · AwareKnows what it is and when it's used
- L2 · BasicsCan use it with guidance
- L3 · WorkingUses it independently on the job
- L4 · StrongHandles hard cases, reviews others
- L5 · ExpertDesigns with it, teaches it
Interviews, by kind of company
Your route adds an interview track that matches the company you choose.
Large IT services firms: aptitude, fundamentals, technical and HR rounds.
Online assessment, coding rounds, a design round.
Hard timed coding rounds, system design, behavioural interviews.
Questions
What does a AI Engineer need to know?
AI Engineer, Prompt Engineering Roadmap, Python Developer at a working level, plus AI Agents, Machine Learning. The skills section above lists every one with its level.
How long does it take to become a AI Engineer?
About 203 hours of study from scratch. At 10 hours a week that's roughly 21 weeks; anything you already know is skipped after the readiness test.
I already know some of this. Do I start from zero?
No. The optional readiness test finds what you already know and your route skips it.
Does the route change for product companies or senior roles?
Yes. Choose your level and the kind of company above: the skills and target levels adjust, for example deeper data structures and system design for product companies.
Other roles in the Data & AI track
They share many skills with this one, so progress carries over if you switch.
Answer questions with SQL, Python and dashboards.
Models and analyses with Python and machine learning.
Pipelines and data platforms.
Deploy and run machine-learning systems in production.