Experience

• Lead backend of a liquid-staking product with $100M TVL and 20k+ users in a team of 8; own architecture and key technical decisions.
• Designed and shipped 10+ smart contracts to production with Python tooling for testing and deployment automation.
• Consolidated 30+ Telegram bots into one autoscaled Kubernetes service, cutting idle memory footprint by ~15 GB.
• Recovered user rewards lost to a legacy accrual bug by recomputing balances from on-chain transaction history.
• Run production launches and incident response on Grafana / Prometheus / Loki, holding 99% uptime.
• Mentor 3 engineers with individual growth plans; drive code-review and release discipline.

Python (FastAPI, Pydantic, SQLAlchemy, Taskiq), PostgreSQL, Redis, Kafka, Docker, Kubernetes, Helm, FluxCD, GitLab CI

• Built backend for AI integrations with multiple LLMs: request routing, response handling, pipeline optimization.
• Engineered a video-analysis ETL pipeline over ~1,900 hours of footage, raising data-processing throughput by 50%.
• Delivered a conference video-recording service; cut recurring errors by 35% with tests and validation.

Python (FastAPI, Pydantic, SQLAlchemy, Celery), PostgreSQL, Redis, Docker, Kubernetes, Helm, ArgoCD, GitLab CI

• Architected a reservation platform integrating TimeKit, SendGrid, and Stripe payments.
• Replaced TimeKit with a custom scheduler, removing a third-party dependency and licensing cost.
• Cut CI/CD pipeline time by 75% (20 min to 5 min).
• Built a Slack bot for real-time GitLab pipeline monitoring.

Python (Django, DRF, Celery), PostgreSQL, Redis, Docker, Kubernetes, Helm, FluxCD, GitLab CI

• Built web-scraping and data-parsing services (Django, pandas, regex) feeding Google Sheets.
• Stabilized a legacy codebase: added test coverage and monitoring.
• Maintained a video-course platform for patient rehabilitation.

Python (Django, DRF, Celery, aiogram, pandas), PostgreSQL, Redis, Docker, GitLab CI