Developer – AI, full-stack, and the bits in-between
Developer with a physics-and-math brain and a knack for building practical tools that turn AI buzz into actual features. Ever since 2020, most of my work revolves around LLMs and image generation, following years of messing with smaller neural networks. This means I don't buy or sell buzzwords, I understand things a level or two deeper than most, and I've developed an intuition for what models can and cannot do.
I've built systems from scratch, simplified convoluted integrations, and turned vague ideas into working prototypes — across open-source, startups, and global advertising giants.
I'm the kind of developer you can generally leave unattended, as long as the overall vector is clear. I have enough life expertise to figure stuff on my own, enough imagination to fill the missing pieces, and a "treat any job as if it was your own brainchild" mentality.
In other words: a surprisingly low-maintenance LLM tinkerer with a TypeScript kink, ready to prototype, debug, or sanity-check your AI-infused ambitions.
I tend to stick to a more "economical" paradigm of AI usage: smaller prompts, more aware of context limitations, less "let's feed it all and it'll somehow work!" My expertise predates the ChatGPT hype cycle, which means I understand not just the APIs, but the underlying patterns and limitations that most "AI engineers" are still discovering.
Read the case studyRead the case study: vovazakharov.com/case-studies/playgram
Rebuilt a live, feature-rich AI chat product — multiple model providers, realtime team chats, image and file libraries, memory and knowledge management, voice input — from Bubble, a no-code builder, into a production Next.js 16 codebase, while it stayed in production for its users throughout.
Delivered in 158 days — parallel AI sessions, up to 20 agents working at once:
Next.js 16, Railway + Supabase, feature-sliced design
AI-powered English learning application for kids, combining generative AI with time-tested pedagogical methodology to make language acquisition engaging and effective.
Next.js, OpenAI API, custom game engine
Short-term project shaping an AI-agent–based review intelligence tool for brand marketing.
Built the system end-to-end, covering:
Next.js/NestJS, Cloudflare Workers, Firebase, custom LLM orchestration framework
Experimental AI platform at one of the world's largest ad firms. Built, back to front, a suite of interlinked AI tools:
Django + PostgreSQL, Vue + TypeScript
Demo available on request.
Selected highlights:
Prototyped bleeding-edge tools for audio + AI experimentation.
Master's in Applied Math & Physics (2000 – 2006)