Starting My Journey Into AI Architecture

From Experience to the Cutting Edge

I have spent over a decade in performance engineering and a year in architecture, in the complicated and busy financial services industry. My current role is a mix of solutions and enterprise architecture. I’ve designed distributed systems, optimized performance, and helped teams solve complex technical problems. But recently, I decided it’s time for a new challenge: diving headfirst into the world of AI and AI architecture.

This blog post is the first of many in what I hope will be a transformative journey, documenting what I’m learning, the hurdles I face, and the plan I’ve put in place to get there.

I am warning you now, I am not the best writer!

Why AI, and Why Now?

AI is everywhere! It's transforming industries, creating new possibilities, and fundamentally changing how we interact with technology. I have come to realize that to remain at the forefront as an architect (and the technology-fanboy in me), I need to understand AI not just as a user, but as an architect.

I am particularly interested in large language models (LLMs) and generative AI, and I want to gain the skills to design AI systems that are scalable, secure, and effective. Real skills that companies like leading organizations like NVIDIA, OpenAI, and Anthropic value.

Needing a Plan

To make this transition meaningful, I recognize I need a structured plan. I’m starting from zero in terms of hands-on AI experience, so the goal isn’t just to tinker but rather to build real understanding:

• Understanding how AI works under the hood, so I can hold intelligent conversations about architecture and model design.

• Gaining enough experience to navigate and influence engineering teams effectively

• Preparing to pursue certifications, such as NVIDIA's AI Infrastructure and Operations, to demonstrate and market my expertise in AI systems.

Learning through Courses and Labs

To get there, I need to map out a learning path that balances theory with practice:

• I will definitely be taking the DeepLearning.AI Generative AI with LLMs Coursera course, based on what I have seen online it provides a clear view into the evolution of generative AI, its capabilities, and the technologies driving it.

• Beyond the course, I plan to engage with hands-on labs to visualize how AI models work, understand tokenization, training dynamics, and inference, and explore how models make decisions under the hood.

The aim is to be an architect who understands what the business and engineers need to succeed, bridging the gap between architecture, AI capabilities, and enterprise implementation.

The Journey Ahead

I’m currently putting together a detailed plan for the next several weeks, mapping out milestones, skills to acquire, and certifications to pursue. This journey is long, but it’s also incredibly exciting. I look forward to sharing the process, the wins, and the lessons learned along the way. I hope that others can benefit from my story.

This is just the beginning.