Meet our alumni: Lyubomir Ivanov, 8-month AI Engineer bootcamp graduate

‍Why this story matters

The AI engineering field is fairly new, and positions are filling slower than employers wish. Lyubomir's story is proof that motivated professionals, whether developers seeking to level up or entrepreneurs with engineering backgrounds wanting to catch the AI wave, can transition into this field. But it demands structured learning, practice, expert guidance, and, of course, motivation.

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Lyubomir, can you tell us about your background before joining the AI Engineer bootcamp?

I have a doctoral degree in pharmacy and spent 11 years teaching at university. Beyond academia, I've worked as a project manager in telemedicine and medical device development. I'm self-employed now, working as a freelancer with startup experience.

I realized that for more complex projects, I need to understand what's happening underneath the surface. AI engineering seemed like a very good opportunity for me. Now that we've finished this study, it's even more attractive to me. I couldn’t imagine then how interesting the field of data science and AI is.

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What made you choose AI engineering specifically?

I am project-oriented and not really a master of coding. I thought AI engineering would fill my gaps. I really admire what JetBrains and Hyperskill do with their study programs. The practical approach combined with thorough theory was exactly what I like.

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How was your experience with the bootcamp?

The first part was excellent. I feel confident about most things we did there. What I really appreciate is that the program is very well developed in terms of consistency and width.

I also appreciate the practical knowledge that gives you a very good start in the profession of AI engineer. The progression from simple LLM API integration to building RAG systems was clear and logical. The multi-agent systems were particularly engaging for me. It was hard to deal with the most complex, scientific part of the studies, for example, about quantization and transformers. It's a bit difficult. It takes some time for the theoretical part to mature in your mind.

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The path to becoming an AI engineer requires dedication, the ability to process complex information, and sustained motivation. But you don't have to do it alone. Our intensive 10-week instructor-led AI Engineer bootcamp provides the structured curriculum, practical projects, and support from AI engineers to successfully transition into AI engineering. Book a free consultation call with us and discover how our bootcamp will help you achieve your goals.

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What skills do you feel confident about now?

For the first part, I'm very confident. I can deal with RAG systems, embeddings, vector databases, LLM integration and evaluation, and multi-agent systems. I understand practical AI application development.

For the second part that covers transformers, neural networks, and convolutional networks, model fine-tuning and compression, I understood the complicated theoretical concepts, however, I need to practice more in writing code for this part.
A few months ago there was an AI workshop organized by the local tech community and looking at its program, I was like: “Come on, we have already covered all workshop topics at Hyperskill!”.

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What was the most valuable insight you gained from the bootcamp?

This bootcamp gave me insights into data science, and I understood that LLMs are not universal. You need to have more capabilities than just prompting LLMs. For data science, you need to do more than this, and many of these skills we already covered here. That's what I like about it.

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What are your plans moving forward?

Originally, my plan was to go back to an old startup project for telemedicine and to integrate ML and LLM in it. The app was created for outpatient support. Currently, I think I need to gain more experience in this field before launching this project.

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What would you tell other professionals considering this path?

The program is very well developed. The practical skills you gain are immediately applicable.

But be prepared: this is not a casual learning experience. The advanced topics are genuinely complex. You need to be highly motivated to succeed. The good news is that with the right materials, project-based learning, and instructor support, it's achievable.

Learn more about instructor-led AI Engineer bootcamp

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