Ростислав

ROSTYSLAV MYSHOK
Backend Python Developer
Lviv, Ukraine | [открыть контакты](см. выше в блоке «контактная информация») | [открыть контакты](см. выше в блоке «контактная информация») | [открыть контакты](см. выше в блоке «контактная информация»)

PROFESSIONAL SUMMARY
Backend Python Developer with nearly 2 years of commercial experience designing and building scalable, production-grade
backend systems. Specializes in REST API development with Django REST Framework and FastAPI, asynchronous task processing
with Celery, and relational data modeling with PostgreSQL. Hands-on experience integrating third-party platforms (AWS Cognito,
advertising APIs, OpenAI API) and applying optimization techniques with Google OR-Tools to solve real business problems such as
dynamic pricing. Comfortable delivering independently on short-term contract work as well as collaborating within cross-
functional teams.
TECHNICAL SKILLS
• Languages: Python
• Web Frameworks: Django, Django REST Framework, FastAPI
• Databases: PostgreSQL, SQLite, Redis
• Async / Task Queues: Celery
• Optimization: Google OR-Tools
• AI / ML Integration: OpenAI API, Prompt Engineering, RAG
• API Documentation & Testing: Swagger / OpenAPI, Postman
• Containers & DevOps: Docker, Docker Compose, CI/CD, Sentry
• Cloud: AWS (Cognito, S3)
• Version Control: Git, GitHub, GitLab
• Deployment & Hosting: Render.com, Koyeb, PythonAnywhere
• Frontend Basics: HTML, CSS, JavaScript
PROFESSIONAL EXPERIENCE
Backend Python Developer — Appexoft | Project: Partnerbrite
Customer: UK company
Involvement Duration: 1 year 2 months
Project Team Size: 12 members — 4 Backend Developers, 4 Frontend Developers, 1 DevOps Engineer, 1 Project Manager, 1 QA Engineer, plus
myself
Tech Stack: Django REST Framework, PostgreSQL, Docker, Celery, Redis, Swagger, AWS, GitHub
B2B platform enabling sports clubs to partner with brands on targeted advertising to their fanbase, with conversion reporting on
ad performance.
Responsibilities:
• Designed and developed scalable REST APIs with Django REST Framework, including ViewSets, serializers, validation,
pagination, and permissions.
• Integrated multiple advertising providers (Google Ad Manager, DV360, Facebook, TikTok, Twitter/X), implementing client
extensions, field mappings, query building, filter logic, and response unification.
• Configured AWS Cognito for authentication and authorization, including JWT validation, protected API access, and role/scope-
based access control; worked with SCIM-based provisioning and SailPoint integration for automated user sync.
• Implemented partial AWS S3 integration for file storage and media handling, including bucket configuration and secure access
management.
• Collaborated with stakeholders to clarify business requirements, ensuring backward compatibility while minimizing changes
through reusable helper functions.
• Optimized API performance through request logging, error handling, IN filters, and pagination for large datasets.
• Wrote and verified unit/integration tests; used Swagger and Postman for API testing and verification.
• Maintained Docker Compose development environments, including environment variables and database migrations.
• Participated in code reviews, API contract discussions with frontend leads, and documentation via Swagger and README
updates.
• Independently designed and built an automated ad-verification pipeline to confirm the presence and authenticity of physical
in-store advertising across retail locations: implemented Celery-based scheduled email delivery with 7-day expiring
submission links, support for arbitrary file formats (photos, video, etc.) with automatic chunking of long videos and GIFs, AI-
prompt-based content verification, and structured result generation — correctly modeling many-to-many relationships such
as a single store manager overseeing multiple stores across different locations.
Backend Python Developer — Appexoft | Project: Reports Automation
Customer: Poland company
Involvement Duration: 6 months
Project Team Size: 4 team members — 1 DevOps Engineer, 1 Project Manager, 1 Frontend Developer, and myself (Backend Developer & QA),
with direct client involvement
Tech Stack: FastAPI, Celery, PostgreSQL, SQLAlchemy, OpenAI API, Pandas, Docker, pytest
Backend service for automatic enrichment of B2B data using AI: ingests Excel files of company lists, processes them
asynchronously, and enriches the data with intent keywords, pain points, and consumer journey stages via OpenAI.
Responsibilities:
• Developed and maintained REST API endpoints with FastAPI for file upload, task creation, status checking, and result
download.
• Implemented asynchronous background processing of Excel data with Celery workers, handling row-by-row enrichment and
task status updates.
• Integrated the OpenAI API for AI-based data enrichment, including prompt engineering, request retries, error handling, and
JSON response parsing.
• Designed and operated the database layer with PostgreSQL and SQLAlchemy, building data models and encapsulating
business logic in service layers.
• Processed Excel files with Pandas for data reading, augmentation, and generating enriched output files.
• Ensured code quality through unit and integration tests written with pytest.
• Managed containerized environments with Docker and Docker Compose; contributed to CI/CD pipeline setup for automated
testing and deployment.
INDEPENDENT PROJECTS
Backend Python Developer (Freelance) — Rules-Based Pricing Engine (MVP)
Customer: USA company
Involvement Duration: ~140 hours (project-based, approx. 3–4 weeks)
Project Team Size: Independent engagement — worked directly with the client (1:1)
Tech Stack: Python, Google OR-Tools, FastAPI, PostgreSQL, Docker
Client-commissioned MVP pipeline covering dynamic pricing, discount optimization, and cost estimation.
Responsibilities:
• Designed and implemented a rules-based pricing engine MVP for dynamic pricing, discount optimization, and cost estimation.
• Built and tuned the optimization model and business rule logic, configuring Google OR-Tools solver parameters for accurate,
low-latency calculations.
• Exposed pricing calculations through a REST API built with FastAPI, backed by PostgreSQL, and containerized the service with
Docker.
• Delivered fast computation times and high pricing accuracy for the client's catalog size at the time of release; recommended
migrating the production version to Rust for further performance gains.
Backend Python Developer (Freelance) — AI Agent Containerization
Customer: Israel company
Involvement Duration: ~1 day (4–6 hours hands-on) to meet a tight client deadline
Project Team Size: Independent engagement — project handed over by another developer; worked directly with the client (1:1)
Tech Stack: Docker, Docker Compose, FastAPI, OpenAI API
Short-turnaround engagement to containerize and run pre-built AI agents for a client demonstration.
Responsibilities:
• Containerized two pre-built OpenAI API-based agents using Docker and Docker Compose, creating an isolated and
reproducible runtime environment for a client demo.
• Wrapped the agents in a FastAPI-based service and ran/interacted with them directly via the Docker console.
• Delivered a working solution within a same-day turnaround, achieving roughly 95% accurate agent interaction without
modifying the underlying agent logic.
EDUCATION
Lviv Polytechnic National University — Computer Engineering
CERTIFICATIONS
• Python Complete Program — SoftServe (Feb 2024 – Nov 2024)
LANGUAGES
• Ukrainian — Native
• English — B2