Ruslan Labza

About

Built and launched a production AI chat assistant inside a data processing platform, focused on helping users understand large table outputs and job results faster. Brings strong end-to-end product engineering across React/TypeScript frontend, backend APIs, and LLM integration, with a clear emphasis on reliability, safe behavior, and iterative quality improvements after launch.

Key Strengths

• Shipped a production AI chat assistant used by real customers
• End-to-end ownership across frontend UI and backend/services
• Strong LLM product design with structured context and guardrails
• Reliability-focused engineering using retries, timeouts, fallbacks, and response validation
• Zero-to-one scoping under ambiguity for AI features
• Cross-functional alignment with product, design, backend, and platform teams
• Performance optimization for large-table workflows
• Iterative post-launch improvement driven by API errors, latency, failed requests, and user feedback
• Improved workflow speed by about 30% for table-related tasks
• Improved development productivity by around 20%
• End-to-end ownership of full-stack features (architecture, routing, API integration, error/loading states, post-launch support)
• Designing hybrid server/client data-fetching patterns for responsive UIs (SSR + client polling/cache updates)
• Handling complex asynchronous workflows with explicit job states and idempotency to prevent duplicate processing
• Postgres schema design with strong constraints and optimized dashboard queries validated via EXPLAIN ANALYZE
• Improving React performance by refactoring state boundaries and applying memoization to reduce re-renders

Experience

Education

Skills

Languages