Владислав

Vladyslav Dashkevych
AI / LLM Engineer & Python Backend Developer
[відкрити контакти](див. вище в блоці «контактна інформація») | LinkedIn | GitHub

SUMMARY
Python backend engineer with 6 years of commercial experience, with the last year focused on production AI/LLM systems. I
design and build RAG pipelines, multi-provider LLM integrations (OpenAI, Anthropic, AWS Bedrock, Gemini), and agentic
workflows using function/tool calling — on top of a solid foundation in scalable REST APIs, async processing, and high-load
backend architecture.

SKILLS
AI / LLM Engineering: OpenAI, Anthropic, AWS Bedrock, Gemini APIs, RAG pipelines, prompt engineering, function calling / tool
use, agentic workflows, vector search (Qdrant, PostgreSQL + pgvector), Claude Code
Backend Frameworks: Django, DRF, Django Channels, FastAPI, Flask, Serverless Framework
Async & Concurrency: AsyncIO, Threading, Multiprocessing, Celery, Aiohttp
Databases: PostgreSQL, MySQL, MongoDB, SQLite, DynamoDB, Redis, Qdrant
Automation & Data Acquisition: Selenium, Playwright, BeautifulSoup, web scraping pipelines
Infrastructure & DevOps: Docker, Docker Compose, Kubernetes, AWS, CI/CD (Jenkins), Sentry, ElasticSearch
Code Quality: Pytest, Mypy, Ruff, Black, SQLAlchemy, Pydantic, Marshmallow
Methods & Tools: Agile, Scrum, Git

EXPERIENCE

Python / AI Backend Developer — NDA, Ukraine 2026 – Present
AI-powered procurement intelligence platform helping organizations analyze and act on procurement data through natural-
language interaction.
● Architecture & backend: designed and built backend services (FastAPI) powering the platform's AI features.
● RAG & retrieval: built RAG pipelines with vector search across Qdrant and PostgreSQL (pgvector), enabling semantic
retrieval over procurement data.
● Multi-provider LLM integration: integrated OpenAI, Anthropic, AWS Bedrock, and Gemini into a single pipeline,
including function calling / tool use for structured, agentic workflows.
● Document intelligence: built an automated PDF report generation system (WeasyPrint) for structured output
delivery.
● Infrastructure: worked with Docker and Kubernetes for containerized deployment; debugged and resolved CI/CD
pipeline failures (Jenkins).
Tools & Technologies: Python, FastAPI, OpenAI, Anthropic, AWS Bedrock, Gemini, Qdrant, PostgreSQL (pgvector), Docker, Kubernetes,
Jenkins, WeasyPrint

Python Developer — Dataox, Ukraine Oct 2025 – 2026
AI-powered search engine and intelligent assistant for a real estate platform, enabling natural-language property search beyond
traditional filters.
● Ownership: owned the project end to end — system architecture, backend development (Django, REST API),
requirements analysis, implementation, testing, and optimization.
● Semantic search: designed and implemented semantic property search using vector embeddings, with search
ranking, relevance tuning, and performance optimization for large datasets.
● LLM integration: integrated the OpenAI Responses API with validation and fallback logic; advanced prompt
engineering for query understanding and structured output.
● Third-party integrations: integrated a client REST API to ingest real estate property data (handling incomplete
documentation), then used it for RAG retrieval and calculating derived property parameters; integrated Google
Maps, Geocoding, and Places APIs to enrich results with location data.
Tools & Technologies: Python, DRF, PostgreSQL, Docker, Celery, Celery Beat, Redis, OpenAI, Qdrant, AsyncIO, Google Maps API, Geocoding
API, Places API
 Python Developer — NDA, Ukraine Sep 2024 – Oct 2025
Desktop application automating interaction with a dating platform, using AI for profile analysis and personalized outreach at scale.
● Full-cycle backend: Django, DRF, Aiohttp, AsyncIO, Threading, Multiprocessing for asynchronous task handling and
scalability.
● AI-driven personalization: intelligent contact selection and dynamic message content generation based on
behavioral patterns.
● Automation: web scraping and browser automation (Requests, BeautifulSoup, Selenium) for seamless external API
and web-interface interaction.
● UI: built the desktop UI (ReactJS, Pywebview) and integrated it with the backend.
● Quality: wrote automated tests covering core business logic; maintained CI and codebase quality (Pytest, Black,
Ruff, Mypy).
Tools & Technologies: Django, DRF, Pywebview, SQLAlchemy, AsyncIO, Threading, Multiprocessing, Aiohttp, Requests, BeautifulSoup,
Selenium, Pytest, Black, Ruff, Mypy, ReactJS

Python Developer — NDA, Austria Aug 2022 – Sep 2024
Live streaming and interactive communication platform with real-time chat and donation-based monetization.
● Real-time systems: built backend services for live streaming, real-time chat, and donation workflows; implemented
an internal messenger.
● AI integration: integrated AI into the sales funnel to improve conversion and retention, including an AI-powered
assistant acting on behalf of streamers.
● Personalization: built a recommendation system for content discovery and viewer engagement.
● Scale: implemented user roles, permissions, and VIP features; optimized database structures and application logic
for high-load scenarios.
Tools & Technologies: Python 3, Django, DRF, Django Channels, JS, jQuery, PostgreSQL, MongoDB, Redis

Python Developer — NDA, Ukraine 2020 – Aug 2022
Multiple projects: a task-management platform for property owners, an AI training/feedback platform, a Telegram news bot, and a
marketing analytics application.
● Task platform: designed backend logic for task assignment and progress tracking, with role-based access control
across owners, managers, and staff (Flask, SQLAlchemy, PostgreSQL, AWS).
● AI feedback platform: built a Django backend for collecting human feedback on AI-generated text to support
iterative model training, with an admin panel for dataset management.
● Telegram automation: built a Telegram bot for scheduled multi-channel news posting (python-telegram-bot,
APScheduler, Dramatiq, AWS).
● Analytics: designed backend architecture for a marketing analytics and reporting application, with caching and
background processing for performance.
Tools & Technologies: Python, Flask, Django, DRF, SQLAlchemy, Alembic, PostgreSQL, Marshmallow, AWS, Sentry, ElasticSearch, Redis,
Celery, GraphQL, Docker

LANGUAGES
Ukrainian — Native
English — Intermediate to Upper-Intermediate (B1+)

EDUCATION
Chernivtsi National University of Yuriy Fedkovych
Master's Degree, Computer Science | 2018 – 2023