How Long Does It Take
to Become an AI Engineer?
The honest answer: 3-6 months for most people with consistent effort.
Your specific timeline depends on your starting point. Here's what's realistic for your situation.
Everyone Promises Different Timelines.
What's Actually Realistic?
Some say 6 months, others say 2 years. You've seen bootcamps promising jobs in 12 weeks and degrees taking 4 years. Who's telling the truth?
You need to plan around your current job and life. You can't commit to something if you don't know how long it actually takes.
You want an honest assessment, not marketing promises. How long did it actually take for people like you?
Your Timeline Depends on Where You're Starting
The World-Class AI Engineer Cohort
I've helped dozens of people transition to AI engineering. Here's what I've seen work in practice, based on starting background.
Assess Your Starting Point
SWE background? 2-3 months. Technical adjacent? 4-6 months. Complete beginner? 6-9 months.
Focus on Implementation
Build projects that prove skills, not just learn theory. This compresses timelines dramatically.
Get Strategic Guidance
The right guidance cuts months off your timeline by avoiding common detours
Meet Your Mentor
My aim has been the same for years: become a world-class AI engineer. Every career move I've made has been measured against that.
I started as a software tester on a $500/month internship in the Netherlands. Taught myself to code, learned to ship real systems, and worked my way to Senior Engineer at GitHub.
Then I left GitHub. I joined an AI research lab as Member of Technical Staff, where I currently build products for secure AI monitoring.
The cohort draws directly from my real experience so you can make progress fast.
I run this special cohort with only a few people because hands-on work with me is what it takes to bring you to become a world-class AI engineer.
Real Results
Vittor
AI Engineer
Built and deployed his portfolio piece, then landed the AI role
"The coaching played a huge part in my success. I focused on AI fundamentals, the certification path, and soft skills like professional writing. Having access to expert guidance gave me confidence during interviews and helped me feel I was on the right path.
I built my own platform (simple but functional) and deployed it on AWS. I used it in my portfolio and showcased it during interviews. The way complex topics were explained, especially the restaurant analogy for AI systems, really stuck with me. Focusing on doing the basics well was absolutely essential."
What You Will Get
8 Weekly Tuesday Sessions
3 hours each for 24 live hours total.
Project Scoping at Kickoff
We set the scope of what you'll ship and the milestones to get there before the live sessions start.
Code Reviews
Reviews of your code from Zen during the cohort.
Lifetime Demo Access
Every architecture demo is recorded and yours to keep.
Demo Day
You present what you built and get feedback from Zen, with a recording you can use in your portfolio.
12 Months Community Access
Included with the cohort.
Every Month of Unfocused Learning Adds to Your Timeline
Frequently Asked Questions
How long if I'm already a software engineer?
2-3 months is realistic. You already have 60-70% of the skills needed: Python, production code, deployment, testing. The gap is primarily AI fundamentals (LLMs, embeddings, RAG) and building 2-3 AI projects. With focused effort and guidance, many SWEs transition in 8-12 weeks.
How long if I'm starting from scratch with no coding experience?
6-9 months is realistic for complete beginners. You'll need to learn Python first (4-6 weeks), then AI fundamentals and implementation (8-12 weeks), then build a portfolio and position yourself (4-6 weeks). It's longer, but absolutely achievable with consistent effort.
How long if I can only study part-time while working?
Add 50% to the timelines above. If you can dedicate 10-15 hours per week consistently, a 3-month timeline becomes 4-5 months. The key is consistency, not intensity. 10 hours every week beats 40-hour weekend marathons followed by weeks of nothing.
How much time will this take?
You'll spend 3 hours every Tuesday in the live session and roughly 3 hours of async work in between, for 8 weeks. The Tuesday session time is fixed.
Can I do this while working full-time?
Yes, most attendees do. The live session is one Tuesday a week and the async work fits around your existing schedule, as long as you can carve out roughly 6 hours a week.
I've signed up for cohorts before and dropped out. How is this different?
It probably isn't, and you should hold the money. Most cohort dropouts are people who couldn't articulate what they were shipping when they signed up. That's why the consult exists, and why I turn down most applications. If we get on the call and you can't tell me what you'll have shipped at the end of week 8, I'll point you to the AI Native Engineer community until you can.
I'm not pivoting careers. I want to build a product. Does this still work?
Yes, the cohort works for people shipping their first serious AI system whether the goal is to land a senior role or to launch a product. The shipped system serves both equally well.
Do I need prior AI experience?
You need to be able to code in Python or TypeScript. Complete beginners can follow the classroom they get access to before the cohort sessions to come in well-prepared.
What does it cost?
It's a four-figure investment that we discuss during the 30-minute consult, alongside whether the cohort is the right fit for your project.
What's the fastest realistic path to becoming an AI engineer?
8-12 weeks for someone with software engineering experience who can commit 15-20 hours per week. The fastest paths involve: (1) personalized guidance to avoid wasted effort, (2) building real projects from week one, (3) strategic positioning for AI-specific roles. Generic courses or bootcamps are rarely the fastest option.
Are there any shortcuts to becoming an AI engineer faster?
The biggest 'shortcut' is avoiding the wrong things: endless tutorial watching, Kaggle competitions (hiring managers don't care), building toy projects instead of production systems. Focus on implementation from day one, get feedback on your work, and position yourself strategically. Guidance from someone who hires AI engineers can cut months off your timeline.
I accept those who have the highest chance of success.
In the 30-minute call we discuss your goals and whether you are ready for the program.