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Vitalii

Python Developer

Considering positions:
Python Developer, Back-end програміст
City of residence:
Lviv
Ready to work:
Lviv, Remote

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CONTACTS Vitalii Duvalo
[open contact info](look above in the "contact info" section) PYTHON DEVELOPER
[open contact info](look above in the "contact info" section)
LinkedIn
SUMMARY
Python Backend Developer with experience building scalable asynchronous
Telegram
services using FastAPI, Django, PostgreSQL, Redis, and cloud infrastructure.
Ukraine, Lviv, remote Specialized in high-load REST APIs, AI-powered search systems, data pipelines,
and third-party integrations. Experienced in designing backend architectures,
improving performance, and delivering production-ready solutions in Agile teams.

SKILLS EXPERIENCE

Backend: Python, FastAPI, Python Developer - Appexoft Mar 2025 – present
Django, Django REST Project: AI Content Navigator — AI-powered semantic search and conversational
assistant over medical e-learning materials (video lectures) for a European medical
Framework, Asyncio,
education platform.
SQLAlchemy Backend: Built an AI-powered semantic search and conversational assistant using
Databases: PostgreSQL, Redis, FastAPI, RAG architecture, Qdrant vector search, and self-hosted LLMs, achieving 96%
recall@5 and p95 latency of 260 ms.
Qdrant Search & RAG: Qdrant vector retrieval with MiniLM embeddings and per-course
Architecture: REST API, isolation; improved recall@5 from 88% to 96% via threshold tuning and LLM query
expansion.
Microservices, OOP, SOLID, Ingestion: Whisper ASR, PyMuPDF/python-pptx parsing, token-aware chunking and
Design Patterns, Repository embedding, run as background jobs.
LLM Integration: Self-hosted Mistral (OpenAI-compatible API) for query rewriting and
Pattern multi-turn chat, with output guardrails, timeouts and fallbacks — no external AI API
AI/ML: RAG pipelines, (GDPR).
Improved code quality through automated testing, static analysis, CI/CD pipelines, and
embeddings, vector search, LLM production monitoring practices.
integrations Auth & DevOps: JWT/API-key auth, Docker, GitHub Actions CI/CD, AWS ECS, pytest
(250+ tests), ruff, Locust load testing.
DevOps: Docker, Kubernetes,
AWS ECS, GitHub Actions, Project: Grailbet — async backend for an online betting & casino platform (users,
GitLab CI/CD wallets, KYC, casino games, notifications).
Backend: Designed and developed asynchronous backend services for an online betting
Testing: pytest, integration
platform using FastAPI, SQLAlchemy, PostgreSQL, and Redis..
testing, load testing Architecture: Developing domain modules (user, wallet, casino) with service/repository
layering, Pydantic v2 schemas, and Alembic migrations.
English: Upper-Intermediate (B2)
Auth & Security: Implementing JWT cookie-based auth, account/IP lockout.
Payments & Integrations: Integrating Fireblocks (crypto deposits/withdrawals), Gigadat
EDUCATION (fiat payouts), SumSub (KYC/AML), and IGD (casino provider) via httpx with webhook
processing.
Lviv Polytechnic National
Async Processing: Using Redis 7 for caching, streams, and arq background workers
University DevOps & Quality: Docker, Kubernetes, GitLab CI/CD, pytest integration tests, Hurl
2023 – Present E2E tests, mypy, and ruff.
Bachelor’s Degree in
Project:Ad Analytics — Developing high-scale asynchronous backend services
Computer Engineering
and automated scraping pipelines for a global leader in advertising.
ADDITIONAL Developed automated scraping pipelines using Scrapy, Selenium, and BeautifulSoup for
collecting and processing large-scale data.
EDUCATION Designing scalable RESTful APIs with Django, DRF and optimizing PostgreSQL ORM
Python course at Mate academy queries.
Building web scraping systems with Scrapy, Selenium, and BeautifulSoup.
(Python, Django, FastAPI, DRF)
Architecting data processing pipelines with Pandas, Redis (caching/queuing), and Celery.
Containerizing applications with Docker and managing version control via Git.
Applying OOP/SOLID principles and writing tests using pytest and DRF APITestCase.
Collaborated with backend, frontend, and product teams to deliver production features
and maintain scalable services.

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