Slava Ukraine
Experience
Summary of Qualifications
Senior Software Developer with 20 years of experience designing and building scalable applications, distributed systems, architectures, and complex workflows. Proficient in JavaScript and TypeScript, with a strong background in frontend(React, NextJS
Extensive AI/ML experience, including hands-on development of modern AI architectures like (RAG, CAG, RAFT, etc), LangChain Agents, and graph-based orchestration using LangGraph. Specialized in building and deploying AI agents with reasoning, memory, and tool integration using MCP.
Creator and educator behind a growing YouTube channel
Additionally, experienced in SEO and performance optimization
React is an open-source JavaScript library developed by Facebook for building fast, interactive, and reusable user interfaces. It uses a component-based architecture and a virtual DOM to efficiently update only the parts of a webpage that change, making applications highly performant and easy to scale. React is widely used for single-page applications (SPAs) and integrates seamlessly with modern development tools and frameworks.
Next.js is a React-based framework that adds powerful features like server-side rendering (SSR), static site generation (SSG ), incremental static regeneration (ISR), API routes, Parallel Routes - allows you to simultaneously or conditionally render one or more pages within the same layout., and built-in performance optimizations. It simplifies the process of building production-ready web applications by handling routing, image optimization, and deployment out of the box. Next.js is ideal for projects that need SEO-friendly pages, fast load times, and a smooth developer experience.
, etc.) and backend technologies. Experience also includes NodeJS, GO, Python, and PHP, broadening the ability to work across multiple programming environments. Expertise spans relational (MySQL, PostgreSQL, etc), non-relational databases (MongoDB, Redis, etc.), analytical(BigQuery), and vector databases (QdrantQdrant is a powerful vector search database designed for high-speed, scalable, and efficient nearst neighbor search over large datasets. It is build for AI, recommendation systems, and RAG-based applications, making it great choice when you need semantic search, image similarity search, and natural language processing (NLP) applications.
, WeaviateWeaviate is a powerful open-source vector database for AI search. It is designed for scalable and real-time similarity search. Unlike Pinecone (which is fully managed) or Qdrant (which is optimized for ANN search),Weaviate integrates structured data, keyword search, and vector search in one system. It’s widely used for retrieval-augmented generation (RAG), semantic search, and recommendation systems — with built-in hybrid search capabilities that make it ideal for LLM-based applications.
, PineconePinecone is a fully managed vector database designed for fast and scalable similarity search in AI applications. It is particularly optimized for retrieval-augmented generation (RAG), semantic search, and recommendation systems, making it a leading choice for integrating with LLMs, OpenAI, and LangChain.
etc.), enabling the development of full-stack solutions that are efficient, maintainable, and performant.Extensive AI/ML experience, including hands-on development of modern AI architectures like (RAG, CAG, RAFT, etc), LangChain Agents, and graph-based orchestration using LangGraph. Specialized in building and deploying AI agents with reasoning, memory, and tool integration using MCP.
Creator and educator behind a growing YouTube channel
I also run a YouTube channel where I share insights, tutorials, and tips on AI. My goal is to create content that educates, inspires, and helps others grow their skills. You can explore my videos, join the discussion, and stay updated on the latest industry know-how.
, where I share technical deep dives and tutorials on AI agent architectures, LangChain, vector databases, and LLM tooling. I delivered a dedicated guest lecture at SoftUni UniversitySoftUni (Software University) is one of the most prominent tech education hubs in Eastern Europe. It offers intensive, practice-based programs in software development, AI, data science, and digital technologies.
With a strong focus on hands-on learning, real-world projects, and career development, SoftUni prepares students for successful careers in the IT industry.
Thousands of professionals and aspiring developers have launched their tech careers through its structured programs and strong community support.
on LangChain and modern AI pipelinesLangChain in Action — build production‑ready AI agents. Tools & function calling, Memory, context, and RAG, Orchestration patterns, Evaluation and monitoring Co‑hosted with Software University (SoftUni). Seminar details
, reaching a broader audience of developers and students passionate about real-world AI applications.Additionally, experienced in SEO and performance optimization
SEO (Search Engine Optimization) is the practice of improving your website so that search engines like Google can easily understand, index, and rank it higher in search results. This includes optimizing on-page elements (titles, meta descriptions, headings, structured data), ensuring your content matches user intent, and improving technical aspects like site architecture, mobile responsiveness, and crawlability. Good SEO helps your site attract more organic (free) traffic and reach the right audience.
Performance optimization focuses on making your website load fast and run smoothly. This involves reducing page load times, minimizing JavaScript and CSS, optimizing images, leveraging browser caching, and using techniques like lazy loading and content delivery networks (CDNs). Faster websites not only provide a better user experience but are also favored by search engines, making performance a critical part of SEO.
Together, SEO and performance optimization ensure your site is discoverable, user-friendly, and efficient, which directly impacts engagement, conversion rates, and long-term growth.
, with a strong track record of improving Core Web VitalsCore Web Vitals are a set of performance metrics introduced by Google to measure the quality of user experience on a website. They focus on three key aspects: loading performance (Largest Contentful Paint – LCP), interactivity (First Input Delay – FID, being replaced by Interaction to Next Paint – INP), and visual stability (Cumulative Layout Shift – CLS). In simple terms, Core Web Vitals track how fast your site’s main content loads, how quickly it responds to user actions, and how stable the layout is while loading. These metrics directly influence SEO rankings, as Google prioritizes websites that provide smooth, fast, and reliable experiences. Optimizing Core Web Vitals not only boosts search visibility but also improves user satisfaction, engagement, and conversions.
, search visibility, and multilingual content strategies by aligning frontend engineering with business-driven marketing goals.Frontend
Proven track record in creating highly responsive and interactive user interfaces using modern frontend frameworks like React, NextJS
Skilled in building high-performance applications with VanillaJS and Web Components, eliminating framework overhead to maximize speed and efficiency. Experienced in implementing Module Federation for scalable, decoupled architectures and seamless microfrontend integration. A strong focus on performance optimization and user experience ensures the delivery of rich, intuitive, and maintainable applications.
React is an open-source JavaScript library developed by Facebook for building fast, interactive, and reusable user interfaces. It uses a component-based architecture and a virtual DOM to efficiently update only the parts of a webpage that change, making applications highly performant and easy to scale. React is widely used for single-page applications (SPAs) and integrates seamlessly with modern development tools and frameworks.
Next.js is a React-based framework that adds powerful features like server-side rendering (SSR), static site generation (SSG ), incremental static regeneration (ISR), API routes, Parallel Routes - allows you to simultaneously or conditionally render one or more pages within the same layout., and built-in performance optimizations. It simplifies the process of building production-ready web applications by handling routing, image optimization, and deployment out of the box. Next.js is ideal for projects that need SEO-friendly pages, fast load times, and a smooth developer experience.
, Vue, Angular, and ThreeJS & Fiber,ThreeJS is a popular open-source JavaScript library for creating and displaying 3D graphics in the browser using WebGL. It simplifies complex 3D rendering tasks by providing ready-to-use tools for building scenes, adding lights, cameras, animations, materials, and models — without needing to write raw WebGL code. With ThreeJS, developers can create interactive 3D experiences, visualizations, games, and animations that run directly in the browser.
React Three Fiber is a React renderer for ThreeJS, meaning it allows you to use ThreeJS within the React ecosystem. It lets you write 3D scenes using JSX, making it easier to manage 3D components in a declarative, React-friendly way. Fiber integrates React’s state management, hooks, and lifecycle features with ThreeJS, greatly improving productivity and maintainability when building complex 3D applications.
for 3D modeling. Some experience building simple mobile UIs in React Native.Skilled in building high-performance applications with VanillaJS and Web Components, eliminating framework overhead to maximize speed and efficiency. Experienced in implementing Module Federation for scalable, decoupled architectures and seamless microfrontend integration. A strong focus on performance optimization and user experience ensures the delivery of rich, intuitive, and maintainable applications.
Backend (Experience with RR and EDA systems)
Backend expertise includes designing APIs and microservices architectures using NodeJS (ExpressJS, NestJS, Fastify), leveraging tools like Docker, Kafka
Apache Kafka is a distributed event streaming platform designed to handle high-throughput, real-time data feeds. At its core, Kafka works as a publish-subscribe system where producers send messages (events) to topics, and consumers read those messages in the order they were stored. Unlike traditional message queues, Kafka is built for scalability, durability, and fault tolerance, making it suitable for processing massive volumes of data across distributed systems. It stores streams of records in a fault-tolerant way and allows applications to process, reprocess, and replay data efficiently. Because of its reliability and performance, Kafka is widely used for building event-driven architectures, log aggregation, data pipelines, and real-time analytics systems in industries such as finance, e-commerce, IoT, and telecommunications.
, RabbitMQ, and CI/CD pipelines (GitHub Actions) to streamline development workflows, ensuring quick iterations and seamless deployment processes. Hands-on experience with microservice communication using gRPC / tRPC / oRPC / GraphQL / REST and the ELK stack for efficient log management and analytics.I have the ability to call a function from GO or Python in a JS file for example, and thereby overcome the limitations of a given language by using a hybrid structure, by using the strengths of other languages that overcome the limitations of the particular base language and thereby greatly increase performance and efficiency of the given application.
A strong foundation in Object-Oriented Programming (OOP) and Functional Programming applied alongside modern JavaScript / TypeScript paradigms to solve complex problems, with a focus on scalability and code readability.
System Design and Architecture
Experience in designing and architecting scalable, distributed systems across various domains. Proficient in microservices, RR(Request-Response) or EDA (Event-Driven Architecture)
What is EDA (Event-Driven Architecture)?
Event-Driven Architecture (EDA) is a software design pattern where applications asynchronously communicate by producing and consuming events. It's characterized by loose coupling between components, enabling real-time responsiveness and efficient handling of dynamic situations. In simpler terms, when something happens (an event), it's broadcast, and interested parties (consumers) react to it without needing to know who triggered the event or even how it was handled., and domain-driven design (DDD), with a strong focus on performance, fault tolerance, and maintainability.
What is EDA (Event-Driven Architecture)?Event-Driven Architecture (EDA) is a software design pattern where applications asynchronously communicate by producing and consuming events. It's characterized by loose coupling between components, enabling real-time responsiveness and efficient handling of dynamic situations. In simpler terms, when something happens (an event), it's broadcast, and interested parties (consumers) react to it without needing to know who triggered the event or even how it was handled., and domain-driven design (DDD), with a strong focus on performance, fault tolerance, and maintainability.
Skilled in implementing robust caching strategies (in-memory, distributed, and HTTP-based) to reduce latency and improve responsiveness. Experienced in handling transactions in distributed systems using patterns like the Saga pattern, two and three-phase commit (2PC, 3PC), and eventual consistency techniques.
Thrives in collaborative engineering environments, communicates complex ideas clearly, and maintains a strong commitment to delivering reliable, future-proof systems under tight deadlines.
AI & ML Development and Agent Architectures
Deep experience in building AI and machine learning systems, with a strong focus on modern AI architectures including Retrieval-Augmented Generation (RAG), Agent-based frameworks, and custom LLM tooling using LangChain and LangGraph.
Skilled in developing end-to-end pipelines for embedding generation and storage, leveraging vector databases like Qdrant, Pinecone, and Weaviate for semantic search, recommendations, and contextual reasoning. Experienced with OpenAI's embedding models like text-embedding-ada-002 and text-embedding-3-small/large.
Proficient in designing and orchestrating AI Agents with tools, memory, and reasoning steps, using graph-based flow control through LangGraph. Adopted and extended the Model Context Protocol (MCP) to modularize agents across components like llm, client, tool, server, and control plane — enabling scalable, debuggable agent workflows in production.
Creator and educator at an active YouTube channel
LangChain is a framework that helps developers build applications powered by large language models (LLMs), like ChatGPT. It connects LLMs to external tools (e.g. databases, APIs, search engines), enabling them toreason, plan, and take action based on context. LangChain simplifies complex workflows like question answering, agents, chatbots, and Retrieval-Augmented Generation (RAG), making it easier to create smart, dynamic AI applications.. The channel serves as both a knowledge hub and a community-driven platform for cutting-edge AI development.
I also run a YouTube channel where I share insights, tutorials, and tips on AI. My goal is to create content that educates, inspires, and helps others grow their skills. You can explore my videos, join the discussion, and stay updated on the latest industry know-how.
where I share technical deep dives on AI architectures, prompt engineering, agent frameworks, vector search systems, and LangChain tutorialsLangChain is a framework that helps developers build applications powered by large language models (LLMs), like ChatGPT. It connects LLMs to external tools (e.g. databases, APIs, search engines), enabling them toreason, plan, and take action based on context. LangChain simplifies complex workflows like question answering, agents, chatbots, and Retrieval-Augmented Generation (RAG), making it easier to create smart, dynamic AI applications.. The channel serves as both a knowledge hub and a community-driven platform for cutting-edge AI development.I was invited by Software University (SoftUni)
SoftUni (Software University) is one of the most prominent tech education hubs in Eastern Europe. It offers intensive, practice-based programs in software development, AI, data science, and digital technologies.
With a strong focus on hands-on learning, real-world projects, and career development, SoftUni prepares students for successful careers in the IT industry.
Thousands of professionals and aspiring developers have launched their tech careers through its structured programs and strong community support.
as a recognized expert in the field to deliver a guest lecture on LangChain and AI Agent ArchitecturesDive into LangChain Building AI Agents from Scratch. Seminar organized with the assistance of Software University (SoftUni).
, where I demonstrated real-world applications, reasoning pipelines, and tool integrations. The channel and talks serve as both a knowledge hub and a community-driven platform for cutting-edge AI development.Committed to practical AI—bridging research and engineering by integrating modern models, retrieval pipelines, and reasoning engines into real-world systems. Comfortable working with OpenAI, Mistral, Hugging Face, and open-source tooling for cost-effective and production-ready AI stacks.
Database Engineering & Optimization
Hands-on experience architecting and managing relational(PostgreSQL, MySQL), non-relational (MongoDB, Redis, Firebase), and analytical (BigQuery) databases in production environments. Proven ability to design normalized schemas, optimize query performance, and ensure data consistency using transactions, indexing strategies, and replication techniques. Skilled in designing event-driven and real-time architectures powered by databases tailored to the use case — from OLTP systems
OLTP (Online Transaction Processing) refers to a class of systems designed to handle a large number of short, atomic, real-time transactions, such as inserting, updating, or deleting records in a database. These systems are optimized for speed, concurrency, and reliability, ensuring that multiple users can perform operations simultaneously without conflicts or data loss. OLTP is commonly used in applications like banking, e-commerce, reservations, and retail, where rapid response times and strict data integrity are critical. Unlike analytical systems, which focus on complex queries and data aggregation (OLAP), OLTP prioritizes high availability and consistency to support day-to-day business operations.
to analytics-ready OLAP setups. In recent years, developed deep expertise in vector databases such as Qdrant, Weaviate, and Pinecone, using them to power semantic search, RAG pipelines, and AI agents. This includes managing embedding pipelines, hybrid search strategies, and integration with LangChain and OpenAI for intelligent retrieval workflows. Continuously focused on scalability, availability, and data modeling best practices across distributed systems.Online Marketing, SEO & Performance Optimization
Experience in driving growth through technical SEO, on-page optimization & Link Building, and content strategy across multilingual websites. Proven ability to improve search visibility, Core Web Vitals, and organic traffic by combining deep frontend performance knowledge (Next.js, Webpack, Lighthouse audits) with SEO best practices like structured data (JSON-LD), semantic HTML, dynamic sitemap generation, and localized hreflang implementations. Strong understanding of user behavior, conversion funnels, and how to align business goals with technical execution. Developed internal tools for keyword analysis and automated SEO checks. Collaborated closely with content creators, designers, and developers to ensure every page performs well on both search engines and real users — across mobile and desktop.
Main Tech Stack:
Other Languages:
Experience with Databases:
MySql:
14+ years
14+ years
MongoDB:
4+ years
4+ years
PostgreSQL
Redis
Vector Databases
Qdrant
Qdrant
Experience with Other Tools:
System Design and Architecture
Vue:
less then 1 year
less then 1 year
GraphQL
Kafka
Docker
Kubernetes
gRPC / tRPC
GitHub CI / CD
Management tools
like JIRA
like JIRA
ELK Stack (Elastic Search)
Three JS
OS: Windows, Linux
GCP, Azure, AWS (Lambda)
Web Servers: Nginx, Apache
UML Modeling: Class, Use Case, Activity, Sequence Diagrams
Lang Chain
Tensor Flow
Blender
Marketing:
Online advertising
Google ads, SEO
SMM:10+ years
Google ads, SEO
SMM:10+ years
Offline advertising
Graphic design, etc.
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