EBANX - Mid-Level Software Production Engineer | Singapore

• Own production reliability for the APAC region — monitoring systems, triaging alerts, coordinating incident response, and serving as one of the key engineering references for merchants and partners operating across Southeast Asia; • Investigate and troubleshoot complex production issues across the stack, including integrations with payment partners such as PSPs, acquirers, and local payment rails; • Support the onboarding, go-live, and stabilization of new payment integrations and market expansions in APAC — participating in new market and product launches from integration all the way to production readiness; • Implement hotfixes for critical production issues and conduct root cause analyses to identify systemic risks and prevent recurrence; • Improve observability coverage for APAC services — building and tuning dashboards, alerts, and runbooks using tools like Datadog and OpenSearch so issues are detected before they impact merchants; • Contribute to the operational foundations of the Singapore Engineering Hub: incident response playbooks, on-call processes, deployment standards, and ways of working; • Identify and mitigate systemic risks in production — through code reviews, post-mortems, and proactive reliability improvements — to reduce incident frequency and revenue impact; • Collaborate closely with EBANX's engineering teams in Brazil to ensure knowledge transfer, consistent practices, and alignment across time zones; • Our stack & work environment: MacOS, GitHub Enterprise, Datadog, OpenSearch, Claude, Devin.ai. • Hands-on experience in production engineering, DevOps, or site reliability engineering — you've owned services in production and know what it takes to keep them healthy; • Strong troubleshooting skills across distributed systems in high-availability, high-throughput environments — you can navigate complex incidents methodically and drive resolution end-to-end; • Solid experience with observability tooling — monitoring, alerting, log analysis, and tracing — with a mindset oriented toward operational excellence and reducing time to detect and resolve incidents; • Practical experience with cloud infrastructure (AWS preferred) and CI/CD-driven environments, contributing to deployment reliability and automation — and naturally reaching for AI tools to work smarter, whether speeding up code reviews, accelerating incident investigation, or building more intelligent alerting;