Volodymyr – Typescript, AWS, Python

A fintech investment platform that processes complex trades in real time and uses predictive AI models to deliver live investment insights to users. Core features include a real-time order management system, automated market data ingestion, and a mobile client that streams live market updates and AI-driven analytics.

• Architected a high-throughput order management system and real-time trading ecosystem using FastAPI, introducing advanced architectural patterns to process complex fintech transactions reliably.
• Engineered automated data ingestion pipelines to aggregate market metrics, seamlessly integrating third-party services and predictive AI models to deliver real-time investment insights.
• Developed a reactive mobile client with React Native and Typescript, implementing robust state management to stream live market updates and AI analytics without blocking the UI.

An enterprise AI platform that lets users run semantic search and "chat with their data" across connected sources like databases, APIs, S3, and Google Drive. A RAG engine ingests and vectorizes large volumes of unstructured corporate data in near real-time, with a secure connector framework enforcing granular per-source permissions.

• Architected a scalable RAG engine enabling enterprise semantic search across heterogeneous connected data sources
• Engineered a high-throughput ingestion pipeline (FastAPI + Celery) that processes, vectorizes, and synchronizes unstructured data in near real-time
• Designed a secure universal connector framework with granular RBAC, abstracting external API complexity while enforcing strict data privacy

An enterprise LegalTech platform that automates Conflict of Interest checks across complex corporate structures, turning manual compliance review into a proactive risk-identification system. Built around a hybrid graph-relational knowledge graph for deep-link analysis, with real-time case updates during client onboarding.

• Architected an automated Conflict of Interest engine, replacing manual compliance checks with proactive risk identification across complex corporate structures.
• Designed a hybrid graph-relational architecture (FalkorDB + PostgreSQL) with automated data-enrichment pipelines, transforming raw entity data into a knowledge graph.
• Built a responsive, type-safe React/TypeScript frontend integrated with WebSockets for real-time case updates and alerts.

A Web3 Telegram Mini-App with hybrid Telegram + WalletConnect authentication, enabling frictionless onboarding and live asset analytics. Includes an internal marketplace for NFT-like royalty trading powered by utility-token smart contracts, plus cross-platform identity unification for richer user profiling.

• Engineered a Telegram WebApp with hybrid authentication (Telegram + WalletConnect) for frictionless onboarding and live asset analytics
• Developed utility-token smart contracts in Foundry, powering an internal NFT-like royalty-trading marketplace
• Unified cross-platform identities (Google, Spotify, X), improving profiling accuracy by 40% and driving a 25% retention increase
• Optimized on-chain data interactions, cutting API latency by 35%

A crypto tracking platform that captures real-time token events across multiple EVM chains to feed a proprietary risk-scoring algorithm. Delivers sub-second updates on asset prices and on-chain transactions, with audited smart contracts for secure wallet tracking and automated portfolio synchronization.

• Engineered a high-frequency blockchain indexing service capturing real-time token events across multiple EVM chains
• Developed and audited Solidity smart contracts (Foundry) for secure wallet tracking and portfolio synchronization
• Built a resilient FastAPI + WebSocket backend delivering sub-second price and transaction updates

A secure MVP for AI-assisted medical diagnostics that helps radiologists and researchers annotate medical imagery faster. The platform integrates AI inference APIs for near-instant image annotation while enforcing strict role-based access control to meet healthcare data compliance requirements.

• Architected and delivered a secure MVP for AI-assisted medical diagnostics, implementing strict role-based access control for healthcare data compliance
• Optimized image processing pipelines, integrating AI inference APIs with FastAPI for near-instant annotation of medical imagery
• Developed a responsive React/Material UI interface, streamlining complex clinical workflows for radiologists and researchers