From Site Reliability Engineer
to AI Engineer
You keep production alive at scale and own the on-call pager.
Now apply that reliability mindset to AI systems and command higher offers.
You Keep Everything Running.
But AI Roles Read Like a Different Language.
You own uptime, SLOs, and incident response, yet AI engineer postings ask for LLMs and retrieval systems you have never shipped.
You are stuck firefighting alerts and toil while teammates pivot into AI work that gets the visibility and the budget.
Pure reliability roles are being absorbed into platform teams, and you worry your hard-won ops experience is getting commoditized.
Reliable AI Is Still Reliability Engineering.
The World-Class AI Engineer Cohort
AI engineers need people who can keep nondeterministic systems healthy in production. You already own observability, error budgets, incident response, and capacity planning. Building AI applications adds LLM APIs, evaluation, and retrieval on top of the operational foundation you already have. The reliability layer that scares most developers is exactly where you are strongest.
Map Your Foundation
Translate SLOs, observability, and on-call rigor into AI system reliability
Add the AI Layer
LLM APIs, retrieval, agents, and evaluation harnesses for nondeterministic output
Own AI in Production
Ship and operate AI systems with the reliability discipline teams desperately need
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 Are Desperate for People Who Can Keep Models Reliable in Production
Frequently Asked Questions
Why are site reliability engineers well-suited for AI engineering?
AI engineering is increasingly a production discipline. Once an AI feature ships, someone has to monitor latency, control cost, handle failure modes, and respond when output degrades. SREs already live in this world. You understand SLOs, observability, incident response, and capacity planning. The new part is understanding LLMs, retrieval, and evaluation, which takes weeks to learn rather than years. Teams want engineers who can keep AI reliable, not just prototype it in a notebook.
What does an SRE need to learn to become an AI engineer?
Focus on applied AI rather than research. The core additions are LLM APIs from providers like Anthropic and OpenAI, vector databases for retrieval, agent and orchestration patterns, and evaluation harnesses that measure quality on nondeterministic output. Your observability, alerting, automation, and on-call experience transfer directly. You do not need heavy machine learning math. You need to learn how to build, ship, and operate AI applications.
Do AI engineers earn more than site reliability engineers?
AI engineering roles often pay at or above senior SRE levels, frequently in the 130k to 180k range and higher at companies with mature AI products. The premium comes from scarcity. Few people can both build AI features and keep them reliable under real traffic. Your reliability background lets you target the operational side of AI teams, where compensation is strong and competition is thinner than for pure model-building roles.
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.
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.