How to Become an
AI Automation Engineer
Automate what humans don't want to do.
AI Automation Engineers build intelligent workflows that save companies millions—earning $120K-$190K+.
AI Native Engineer Community Access
Want to Build AI That
Actually Does the Work?
Companies waste thousands of hours on repetitive tasks. You see the potential for AI automation but don't know how to connect the pieces.
AI automation requires integrating LLMs with real business systems—CRMs, ERPs, databases. The technical challenges are non-obvious.
Businesses pay premium rates for automation that works. But building reliable, production-grade automation is harder than it looks.
The AI Automation Engineering Path
The AI Career Accelerator
AI Automation Engineers combine LLM skills with systems integration and workflow design. Here's how to build this high-impact specialization.
Master LLM Fundamentals
Build strong foundation in prompt engineering and API integration
Learn Integration Patterns
Connect AI with databases, APIs, CRMs, and enterprise systems
Build Workflow Systems
Design multi-step automations with error handling and monitoring
Deploy Production Automation
Create reliable, maintainable automation that runs 24/7
Meet Your Mentor
When I started in tech, I was based in the Netherlands with no connections and only thousands of video game hours under my belt. Not exactly the ideal starting point.
My first tech job was software tester. One of the most junior roles you can start with. I was just happy someone took a chance on me.
I kept learning. Kept pivoting. But what actually accelerated my career wasn't more certifications or more code. It was learning to solve problems that matter and proving beyond a doubt that what I built solved real problems. That's the skill that stays future-proof, even with AI.
I've since worked remotely for international software companies throughout my career. Proof that the high-paid remote path is possible for anyone with the right skills and motivation. In the end, I went from a $500/month internship to 6 figures as a Senior AI Engineer at GitHub.
Now I teach over 22,000 engineers on YouTube. Becoming an AI-Native Engineer is a system I lived through and offer to you today.
Real Results
Vittor
AI Engineer
Landed his first AI Engineering role in 3 months
"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
Personalized Roadmap & Career Strategy
A custom plan tailored to your background, goals, and timeline. No generic advice.
Weekly 1:1 Coaching Calls
Direct access to Zen for guidance, project feedback, and answers to your questions.
Portfolio-Ready AI Projects
Build production-grade AI applications to showcase to employers. Work that gets you hired.
Interview Prep & Mock Interviews
Practice technical and behavioral interviews. Learn what hiring managers look for.
Resume & LinkedIn Optimization
Transform your online presence to attract recruiters. Stand out from other applicants.
Community Career Support
Join the AI Native Engineer community. Not seeing results yet? You stay and keep going. We're with you through the ups and downs.
Every Company Has Processes That Should Be Automated. AI Automation Engineers Make It Happen.
Every month you delay can cost you thousands in lost earning potential. While you're watching tutorials, others are landing $120K+ AI Engineering roles.
I can only work with a limited number of 1:1 clients at a time to ensure you get the personalized attention you deserve.
Frequently Asked Questions
What does an AI Automation Engineer actually do?
AI Automation Engineers build systems that handle repetitive tasks automatically using AI. Common projects: document processing pipelines, email triage and response, data extraction and entry, report generation, customer onboarding flows, compliance monitoring, and invoice processing. You identify manual processes, design AI-powered replacements, integrate with existing systems, and ensure reliable operation. The goal is saving human time while maintaining quality.
What skills do I need for AI automation?
Core skills: Python programming, LLM APIs, prompt engineering. Integration: REST APIs, webhooks, database queries, authentication flows. Automation-specific: workflow design, error handling, retry logic, monitoring. Tools: n8n, Make, Zapier for rapid prototyping; custom Python for production. Business understanding: knowing what processes matter and why. The best automation engineers think about reliability as much as capability.
What do AI Automation Engineers earn?
Entry-level: $95K-$130K (1-2 years). Mid-level: $130K-$165K (3-5 years). Senior: $165K-$200K (5+ years). Lead/Principal: $190K-$240K+. Consulting rates for automation projects: $100-$200/hour. Companies often measure automation value by time saved—a good automation project can have massive ROI, which justifies strong compensation for those who deliver it.
How is AI Automation different from general AI engineering?
AI Automation is more integration-focused. While general AI engineering might focus on model performance or novel applications, automation engineering focuses on connecting AI to real business systems and making it reliable. You deal with: API rate limits, authentication, data format mismatches, error recovery, and monitoring. It's less cutting-edge AI and more solid engineering that delivers business value.
How do I start in AI Automation?
Find a repetitive task you do (or your company does) and automate it. Start simple: email summarization, document extraction, report generation. Then add complexity: multi-step workflows, error handling, scheduling. Tools like n8n or Make let you prototype quickly before building custom solutions. The key insight: automation value comes from reliability, not complexity. A simple automation that runs perfectly is worth more than a complex one that fails.
What tools do AI Automation Engineers use?
No-code/low-code: n8n (open source), Make, Zapier for prototyping. LLM APIs: OpenAI, Claude for AI processing. Orchestration: Temporal, Prefect, custom Python for complex workflows. Integration: REST APIs, webhooks, database connectors. Monitoring: custom dashboards, alerting systems. Document processing: LangChain, LlamaIndex for parsing. Production automation often uses Python scripts with scheduled runs via cron, GitHub Actions, or cloud functions.
What background do I need for AI automation?
Ideal backgrounds: backend developer, DevOps engineer, or anyone who's built integrations. You need solid programming skills and API experience. Business analysts who learn to code can be excellent—they understand the processes to automate. RPA (Robotic Process Automation) experience transfers directly. The key is understanding both technical implementation and business process improvement.
How long does it take to become an AI Automation Engineer?
From developer: 2-4 months (learn LLM APIs, build automation projects). From business analyst: 6-9 months (learn programming, then AI and integration). From scratch: 9-12 months (programming fundamentals, then AI and automation). Building 3-5 real automations that solve actual problems demonstrates competence. Portfolio projects that show before/after time savings are compelling to employers.
What if I don't land interviews in 90 days?
You become a member of the AI Native Engineer community, and you stay and keep going. Career transitions take different amounts of time for everyone, and I'm not going to abandon you if things take longer. You get ongoing support through good times and bad.
How is this different from online courses?
Online courses give you content. 1:1 coaching gives you a personalized roadmap, direct feedback on your work, career strategy, interview prep, and accountability. You get answers to your specific questions and guidance tailored to your unique situation instead of generic advice meant for everyone.
What's the investment for 1:1 coaching?
Investment details are discussed during the 30-minute strategy call, where we'll assess your goals and create a custom plan. The program is designed to pay for itself quickly through your increased salary. Most AI engineers see a 20-50% pay increase.
Can I do this while working full-time?
Absolutely. Most of my clients work full-time and make steady progress. We'll schedule calls at times that work for you and create a realistic plan that fits your schedule. Consistency matters more than intensity.
Ready to Land Your AI Role?
Stop watching others succeed. Start building your AI career today.
30-minute strategy call • Limited spots available