Vietnam's leading fintech platform with 16M+ users and 100+ integrated services
Zalopay operates a diversified payment ecosystem serving over 16 million Vietnamese users across domestic and international transactions. The tech stack reveals a modern, frontend-heavy architecture (React, TypeScript, Next.js) paired with enterprise infrastructure (Kubernetes, Airflow, Spark), but the pain-point pattern shows friction in scaling: high-traffic payment systems, manual operation workflows, and frontend observability gaps. Adopting OpenTelemetry signals a push toward better visibility. The hiring mix—engineering and marketing leading, with deliberate AI and security roles—reflects a company pivoting from transaction volume toward operational automation and fraud prevention.
Zalopay is Vietnam's largest fintech platform, built as a core asset within VNG Corporation. The platform facilitates payments, money management, and financial services across 100+ integrated offerings—from peer-to-peer transfers to merchant processing to cross-border settlement. With 501–1,000 employees based in Ho Chi Minh City, the company operates under State Bank of Vietnam regulation and manages high-traffic domestic and international payment flows. Recent project expansion into AI agents, recommendation systems, and merchant dashboards indicates a shift toward operational intelligence and merchant enablement beyond core payments.
Frontend: React, TypeScript, Next.js, Redux. Backend: Python, Java, Apache Airflow, Apache Spark. Infrastructure: Kubernetes, Docker, Terraform. Testing: Jest, Cypress, Playwright, Selenium. Currently adopting OpenTelemetry for observability.
Core: modern payment experiences, cross-border payment portals, merchant dashboards. Growth: AI agent platform, fraud detection AI, recommendation systems. Compliance: State Bank of Vietnam regulatory alignment.
Zalopay's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.