How to Go From Software Engineer
to AI Engineer in 8 Weeks
You've got years of solid engineering experience, but every AI job posting asks for skills you don't have yet.
Stop starting from scratch. Leverage your existing skills to land a $120K+ AI role.
Your Engineering Experience Should Be an Advantage.
Instead, It Feels Like You're Starting Over.
You've shipped production code for years, but AI job descriptions make you feel like a junior again.
You've completed ML courses, but you still can't bridge the gap between tutorials and real AI engineering work.
Junior AI engineers with half your production experience are getting offers while you get ghosted.
Your Software Engineering Skills Are Your Secret Weapon.
The World-Class AI Engineer Cohort
Most ML candidates only know Jupyter notebooks. You already understand production systems, debugging, testing, and deployment. We'll build on your foundation to fill the AI-specific gaps in weeks, not years. Check out our [software engineer to AI engineer learning path](/learning-path/) for a detailed roadmap.
Map Your Skills
Identify what transfers (70%+) and what to add
Build AI Projects
Create production-grade ML systems, not toy demos
Position & Land
Leverage your SWE background to stand out
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 You Wait Costs You $10K+
Frequently Asked Questions
What skills do I already have that transfer to AI?
More than you think. Production Python, data structures, API design, testing, CI/CD, version control, and deployment experience all transfer directly. The gap is primarily ML fundamentals, model training basics, and MLOps patterns. This typically takes 8-12 weeks to fill with focused effort.
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.
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.
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.
How long does the SWE to AI transition typically take?
With your software engineering background, you're already ahead. Most SWEs can make the transition in 2-3 months with focused effort. Compare that to career changers who need 6-12 months. Your production experience is a genuine competitive advantage.
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.