Solutions Architect to AI Engineer
Your Architecture Skills Are Gold.
You've designed systems at scale. Now learn to design intelligent ones.
Your architecture background is the perfect foundation for AI engineering.
The Architect's AI Dilemma.
You design systems but don't implement them. AI roles demand hands-on coding every day.
You know distributed systems, not neural networks. The ML math feels like a foreign language.
Your breadth is impressive, but AI teams want depth. Generalist experience doesn't translate directly.
Architecture to AI in 3-6 Months.
The World-Class AI Engineer Cohort
Solutions architects have an unfair advantage in AI: you already think in systems. You understand scale, reliability, and integration. Now you just need to add AI-specific depth. Here's how to leverage what you already know.
Reclaim Your Coding Edge
Hands-on Python, model APIs, prompt engineering
Add ML Fundamentals
Just enough theory to design AI systems intelligently
Build & Position
Production AI projects that showcase architecture + AI
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.
AI Teams Need Architects Who Code.
Frequently Asked Questions
Do solutions architects have an advantage in AI?
Absolutely. Most AI engineers lack system design experience. They can build models but struggle with production concerns—scale, reliability, cost, observability, integration. You have that already. The gap is hands-on coding and AI-specific knowledge. That's learnable in months. Your architecture mindset takes years to develop and can't be taught quickly.
How do I get back to hands-on coding?
Start with daily coding practice—even 1 hour matters. Focus on Python and AI-specific patterns: API integrations, async programming, data pipelines. Build real projects, not tutorials. Contribute to open source. The goal isn't to become a senior dev again; it's to be dangerous enough to prototype and review code effectively. Many AI architect roles value design skills over raw coding speed.
Will I take a pay cut transitioning to AI?
Usually no—often you'll see an increase. Senior solutions architects typically earn $150K-$200K. AI engineers with production architecture experience command $180K-$280K+ in 2026. The combination is rare and valuable. Companies pay premiums for engineers who can both design AI systems AND understand enterprise architecture. Position yourself at the intersection.
What job titles should I target?
Look for: AI Solutions Architect, ML Platform Engineer, AI Infrastructure Engineer, LLM Engineer, or AI Engineer with a focus on production systems. Avoid pure research roles or positions requiring deep ML theory. Your sweet spot is building and deploying AI systems at scale—not training models from scratch.
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.
Am I too senior/old to switch to AI engineering?
Your seniority is an asset, not a liability. AI teams are desperate for experienced engineers who understand production systems, enterprise constraints, and stakeholder management. Junior AI engineers are common; senior ones who can architect end-to-end solutions are rare. Companies pay more for the combination of AI skills and battle-tested architecture experience.
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.
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 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.