Illia B.Private profile: Upwork shows its earnings only to signed-in members, so we check it every few weeks, not daily. MRR here is a rough estimate (Upwork's six-month earnings ÷ months active). Last read Nov 7, 2026.

I build high-performance backend systems that handle real-time financial data at scale. For the past 2+ years I've been a core backend engineer on a production multi-chain trading platform — Microservice architecture for 4 blockchains (Ethereum, Base, BSC, Solana). What I've shipped: — Reduced token processing time from 39s → 800ms by identifying RPC multicall bottlenecks, redesigning pool selection logic, and adding targeted DB indexes — Cut trading menu response time from 2500ms → 500ms through parallel request architecture and unified backend aggregation endpoints — Migrated copy-trade detection from 30s polling → 50ms via WebSocket block subscription — rebuilt listener service with 4-level rate limiting and automatic wallet deactivation — Designed DEX pool scoring system (BullMQ + PostgreSQL) for optimal liquidity pool selection without expensive per-request on-chain calculations — Fixed systemic PnL calculation bug caused by native/USD price desync — rewrote logic across 9 DB models and 7 services — Stress-tested with 20,000 simultaneous tokens with no job accumulation; 1000 concurrent users at 94% success rate — 2150+ unit tests across swap, copytrade, PnL, statistics, positions and referral modules Also built a full-stack e-commerce platform from scratch — product catalog, CRM, AI consultant (trained on business data, places orders from chat), live operator chat via Socket IO, Nova Poshta integration, payment systems, analytics — solo from architecture to production on AWS. Stack: Node.js, TypeScript, PostgreSQL, Redis, Apache Kafka, BullMQ, Docker, Kubernetes, AWS (EKS, RDS, Secrets Manager), gRPC, WebSocket, REST, Socket IO I write tests before I merge, document what I build, and review teammates' PRs. I debug distributed system failures under production load and propose architectural solutions that get shipped. I actively use AI tools (Claude, LLM agents) in my daily workflow — context management, code review assistance, automated documentation — which noticeably speeds up delivery. Best fit for: fintech startups, trading platforms, high-load SaaS, e-commerce backends, crypto infrastructure.