Sudono T.

Background

About Sudono T.

Backend Engineer | Fintech Innovator | Scalable Systems Builder I’m a driven backend engineer with 5+ years of experience (since July 2019) building scalable, high-performance systems that power real-world products. I specialize in Golang, TypeScript, PostgreSQL, Redis, Firestore, and Google Cloud Platform. Whether shipping greenfield MVPs or optimizing mission-critical services, I focus on delivering backend systems that are fast, reliable, and built to scale. Current Focus: Core Backend Engineer at Amartha I help build and enhance Amartha’s Loan Origination System—from NPL scoring to partner dashboards and internal automation. I work extensively with Gin, Echo, Firestore, Firebase, and Bitbucket Pipelines in a microservices environment. I also leverage modern AI tools (ChatGPT, Cursor, GitHub Copilot) to accelerate development, improve code quality, and support collaborative problem-solving across the team. Impact Highlights - System Architecture: Collaborated with lead engineers to refactor backend architecture—improving clarity, maintainability, and onboarding speed- Operational Efficiency: Led development of a Loan Origination Dashboard, significantly reducing loan processing time for internal teams and partners- Robust Integrations: Built resilient workflows with retry and idempotency mechanisms for third-party API and financial operations- Rapid MVP Delivery: Delivered a complete POS system MVP in under 2 weeks, enabling mom-and-pop stores to digitize daily transactions- Team Enablement: Conducted internal knowledge-sharing sessions on Go automation and generic programming to elevate engineering capability. AI-Enhanced Development: Applied AI-assisted tooling to speed up feature development, improve debugging efficiency, and streamline documentation. I thrive in fast-paced, product-focused environments where engineering excellence directly drives business outcomes. I’m passionate about solving complex problems, writing clean code, and building resilient backend systems that scale.