As generative AI continues to reshape the way we build and scale digital solutions, staying ahead requires both curiosity and commitment to continuous learning.
Our colleague Djordje Savic, Software Engineer from Zrenjanin, has recently earned the AWS Generative AI Developer – Professional certification, and is among the first 5,000 professionals worldwide to receive the Early Adopter badge – a recognition that highlights both the complexity of the exam and the speed at which it was achieved.
In this interview, he shares what motivated him to pursue the certification, how he approached the preparation process, and what this achievement means for his work and for Levi9.
Here’s what Djordje had to say about this achievement and the journey behind it.
What does this certification mean to you, especially considering that you are among the first 5,000 people in the world to earn it?
“When AWS announced the beta version of the Generative AI Developer Professional exam late last year, it immediately caught my attention. It felt like something that matched very well with the direction I have been most interested in for a while now – generative AI and cloud. At the beginning of the year, I set it as a personal goal, with the intention of achieving it by April.
I am very happy that I managed to do it, and this certification really means a lot to me. The fact that this is a professional level exam makes it even more meaningful to me, because it is designed to test not just service knowledge, but also architectural thinking, trade-offs, and production level decision making. It gave me the feeling that I had validated my knowledge in an area that is both highly relevant and genuinely difficult.
The whole story became even more fun with the Early Adopter badge, awarded only to the first 5,000 people who pass the exam. That gave the whole thing an extra layer of challenge and made it feel even more special. My kids were wondering why I was so focused on it, hard working on exam day and night, but once I explained that I was chasing a rare badge that only a limited number of people worldwide would earn, they completely understood. That is probably something only geeks and kids really understand.”
What motivated you to pursue the AWS Generative AI Professional certification?
“For some time already, I had been working and experimenting with generative AI application development, but mostly at a more local level. I wanted to go deeper into it all – to better understand what it really takes to build these solutions properly, how they behave in a serious cloud environment like AWS, and what kind of engineering and operational thinking sits behind them.
Of course, there was also a career aspect to it. This is the direction I want to continue growing in, so the certification felt like a good way to push myself, make that investment more concrete, and prove to myself that this is not just a surface-level interest, but something I am genuinely serious about.”
What was your preparation process like – what did you find most challenging, and what was the most valuable?
“My preparation process had several phases. I started with a Udemy video course, then moved on to AWS Skill Builder content and practice exams. Once I saw which areas were weaker for me, I kept going back to them and studying them more deeply through AWS materials, documentation, and blog posts.
After that, a big part of the preparation became learning directly from the questions. I spent a lot of time analyzing mistakes in detail and trying to understand not only why one answer was correct, but also why the others were not. I also used AI as a kind of study sparring partner, which helped me a lot in breaking down difficult questions, checking my reasoning, and getting better at spotting the small details that can completely change the answer.
The hardest part for me was that many of the questions were not straightforward at all. More than one answer can seem reasonable at first glance, so you really have to weigh trade-offs, constraints, and the exact wording of the question very carefully. On top of that, this is a Professional-level exam, so the questions are difficult by design, and the beta version made it even more demanding because it had more questions than the standard format. Time management was therefore a big factor throughout the whole experience.
What I found most valuable was that the whole process pushed me to think in a much more practical way – less in terms of isolated AWS services, and more in terms of architectural decisions, trade-offs, and patterns from real implementations and real-world problems.”
Why is this important for Levi9? How do you see the application of generative AI in our work and projects?
“I think this is important for Levi9 because the company already has a strong AWS foundation and clear AWS partner positioning, with many certified engineers and proven experience across different AWS programs and competencies. In that context, I see this certification as one more way to strengthen that profile in an area that is becoming increasingly relevant for clients – building generative AI solutions on AWS in a serious, practical, and production-ready way.
I see the application of generative AI both internally and in client projects. Internally, it can help with better access to knowledge, support in development workflows, documentation, and faster prototyping. In client work, I see value in assistants, document-heavy workflows, search and retrieval, summarization, recommendation support, decision-support scenarios, and agentic workflows that can orchestrate multiple steps, use tools, and automate parts of more complex processes.
What matters most to me is that we understand how to do all of this at a production level. It is not only about prompts and models, but also about everything around them – logging, audit, compliance, security, scalability, observability, and cost optimization. Those are the things enterprise clients really care about once GenAI applications move beyond demos and into real business use.
I think that is where this certification fits best for Levi9 – not as something isolated, but as part of a broader capability we can offer to clients: combining AWS knowledge, practical engineering, and a better understanding of how to design and deliver generative AI solutions the right way in real projects.”
This achievement goes beyond an individual milestone – it reflects the direction in which both technology and our industry are moving.
By continuously investing in knowledge and exploring new capabilities such as generative AI, we strengthen our ability to deliver meaningful, production-ready solutions for our clients.
Congratulations once again, and we look forward to seeing how these insights will shape future projects and innovations within Levi9.
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