Дмитрій
AI engineer
- Розглядає посади:
- AI engineer, ML engineer
- Вік:
- 21 рік
- Місто проживання:
- Харків
- Готовий працювати:
- Дистанційно
Контактна інформація
Шукач вказав телефон , ел. пошту та LinkedIn.
Прізвище, контакти та світлина доступні тільки для зареєстрованих роботодавців. Щоб отримати доступ до особистих даних кандидатів, увійдіть як роботодавець або зареєструйтеся.
Отримати контакти цього кандидата можна на сторінці https://www.work.ua/resumes/18718821/
Завантажений файл
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automation workflows for real business tasks. I have delivered 7+ freelance, academic
FENDRYKOV and project-based tasks — AI assistants, backend modules, ML projects, automation
AI ENGINEER flows and working MVP prototypes. Comfortable across the stack: Python, REST
APIs/JSON and Docker on the engineering side; OpenAI API, Claude, RAG,
[
hood — context, tokens, function/tool calling — and know when a task needs fine-tuning
[
versus when prompt engineering is enough. Well versed in Claude, Claude Code and
Ukraine, Kharkiv Codex, with a solid grounding in ML. I know how to integrate AI into Telegram bots, APIs
[
901329343/
github.com/DimaFendrikov WORK EXPERIENCE
AI Engineer & Python Backend Developer Feb 2024 – Present
SKILLS Independent Projects & Freelance
Delivered 7+ freelance, academic and project-based AI/backend tasks — from
Python requirements to working MVPs, prototypes and backend modules;
Built a FastAPI-based RAG assistant for GitHub repository analysis: file processing,
AI Engineering
chunking, embeddings, vector search, context retrieval and LLM-based answers;
LLM APIs Developed an n8n-based AI workflow for vacancy analysis: requirement extraction,
profile matching, match scoring and explanation generation;
OpenAI API Built backend modules (FastAPI, Django) with REST APIs, JSON-based integrations,
CRUD workflows, authentication, database logic and admin panels;
Claude & Claude Code
Worked with core LLM concepts — context windows, tokens, function/tool calling — and
Function / Tool Calling OpenAI/Claude APIs to design reliable, production-ready assistant logic;
Evaluated fine-tuning vs. prompt engineering on a per-case basis (incl. voice agent
Fine-Tuning scenarios, where prompt engineering was the critical lever), balancing accuracy, cost and
latency;
Prompt Engineering
Integrated external APIs and messaging platforms (Telegram Bot API and others) to
connect AI logic to real user-facing interfaces;
RAG
Used Docker for containerized deployment and Git for version control across all projects;
Embeddings use Claude Code daily for AI-assisted development, debugging and code review.
FastAPI PROJECTS
REST APIs, JSON n8n AI Vacancy Analysis Workflow Nov 2025 – Dec 2025
Built an AI automation workflow that analyzes job descriptions, compares requirements
Docker, Git
with a user profile and generates a match score with a short explanation;
API Integrations Implemented workflow automation logic with triggers, data processing, an AI step, result
formatting and user-facing output.
Automation Workflows
CodeMentor RAG – AI Assistant for GitHub Repository Oct 2025 – Nov 2025
n8n Understanding
github.com/DimaFendrikov/codementor-rag
Developed a FastAPI-based RAG assistant that automates GitHub repository
LANGUAGES understanding through file processing, chunking, embeddings, ChromaDB, vector search
and LLM-based answers;
English B2
Implemented context retrieval, prompt-based response generation, quiz generation, a
Ukrainian Native web interface and Docker support, turning raw repository files into an interactive AI
assistant prototype.
EDUCATION
Erasmus+ Exchange Student Feb 2025 – Jan 2026
Alpen-Adria-Universität · Klagenfurt
Bachelor’s Degree in Intelligent Systems and Computer Sep 2022 – Jun 2025
Science
National Technical University «Kharkiv Polytechnic Institute»
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