Solutions Architect to AI Engineer
Your Architecture Skills Are Gold.

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.

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.

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.

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.

Most clients invest 10-15 hours per week, but this can be flexible based on your schedule. We'll have weekly 1:1 calls plus time for you to work on projects and learning. The key is consistency. Regular, focused effort beats occasional marathons.

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.

Not necessarily. While some programming experience is helpful, many of my clients have successfully transitioned from web development, data science, or other technical backgrounds. We'll assess your current skills during our strategy call and create a personalized plan that meets you where you are.

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.

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.

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.

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.