Vlad Chivu
AI Software DeveloperVlad designs and maintains intelligent web crawlers and change-detection pipelines to keep programme and scholarship data accurate at scale; applies AI/LLM-based extraction where it meaningfully improves quality and speed; builds resilient ETL workflows and monitoring to triple operator productivity; and optimizes end-to-end workflows with cost-effective automation. He leverages proven experience with backend services, data handling, Dockerized deployments, CI/CD, and observability to deliver reliable, measurable outcomes.
He is a full-stack/AI engineer with a Computer Science foundation and strong business acumen, specializing in data handling, automation, and ML/LLMs. Recently, he has built AI-driven automation using local/private LLMs, LangChain, RAG, and ETL with containerized, instrumented pipelines. Previously, he owned the backend development for a property-management start-up in Copenhagen. His toolkit spans JavaScript/TypeScript, Python, Node.js/Express, React/Next.js, Django/Flask; and SQL/NoSQL databases, all deployed on Linux, Docker, and cloud platforms.
He aims to scale trustworthy web data collection across thousands of sources overcoming anti-bot defenses, schema drift, and data freshness issues while measurably tripling Data Operator productivity through AI-assisted extraction and streamlined, observable workflows.
He likes to chat about history, sci-fi scenarios or the latest AI tools.
He loves Bachelorsportal transparent search and compare experience, powerful filters, standardized programme pages, and clear scholarship visibility that helps students quickly narrow choices.