Eduardo Mota

"We need to serve customers better, and we can't scale the department at the same rate we are acquiring customers". This was the trigger from my boss that got me to build my first ML system 15 years ago at a contact centre. Eve was its name.

Video TLDR

Not only did it helped us solved emails faster, route interactions properly, manage our phone and chat system, but it also gave me first hand experience on how AI can improve the customer experience when done properly.

I'm not gonna lie, there were hiccups. Like when it encountered an encoding issue with a new language and it stopped working for 2 days backup the email queue to 2k emails when the normal queue would be 500. These learnings didn't make me turn away from the technology, but continue working in improving it.

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Life at DoiT

I’m in a place where I get to express every part of who I am on a daily basis—understanding how systems behave, how machine learning models actually produce value, and how to leverage that value efficiently in the real world.

I’m a Sr. Cloud Data Architect and AI/ML specialist helping enterprises design, build, and operate production-grade cloud and generative AI systems.
My work sits at the intersection of:

• Hands-on architecture
• FinOps-aware design
• Strategic advisory
• Business strategy

I partner with customers to modernize data platforms, adopt generative AI responsibly, and bring cloud costs under control—while building internal capability so their teams can operate and evolve these systems long after I’m gone.

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Impact, teaching, and public work

My dream has always been to build something so meaningful that it positively impacts the lives of thousands of people, and over time I’ve had the chance to design solutions that move the needle for real teams and customers.

One of the most fulfilling ways I do that now is through teaching and up-skilling.
I lead live online trainings with O’Reilly on building AI applications and RAG systems with AWS Bedrock, and I serve as an instructor for Udacity programs on large language models and generative AI.

I speak regularly at industry events, including Google Next and AWS Community Day, and I’ve appeared on podcasts and in publications to talk about:

• The evolution of AI
• Practical ML architectures
• What it really takes to run AI in production

My style is pragmatic and no-nonsense, but personal too: I like to take complex ideas and turn them into clear, actionable guidance that helps both executives and engineering teams make better decisions—and, hopefully, leave feeling a more capable than when they walked in.