Senior Technical Support Engineer

About the Role

As an Advanced Intelligent Support Engineer, you will solve complex, high-impact technical issues for TiDB customers across all deployment models. You will combine deep database expertise, AI engineering, customer engagement, and end-to-end technical ownership to drive issues from investigation through mitigation and resolution.

You will also build scalable proactive and reactive support capabilities through AI agents, reusable diagnostics, automation, knowledge, and product improvements.

Responsibilities

• Lead the diagnosis and resolution of complex customer issues across TiDB, distributed databases, and cloud environments.
• Take technical ownership of critical cases and incidents, working with customers, Frontline Support, Product, and Engineering teams.
• Develop AI agents and AI-assisted workflows that improve diagnosis, troubleshooting efficiency, and knowledge reuse.
• Build proactive and reactive capabilities by identifying recurring risks, developing reusable diagnostics and automation, and turning customer insights into actionable feedback and improvements for Support, Product, and Engineering.

Qualifications

• At least 8 years of experience in database engineering, distributed systems, site reliability engineering, technical support, or a related field.
• Strong knowledge of relational databases such as MySQL, PostgreSQL, or Oracle, with proven ability to diagnose complex production issues using logs, metrics, traces, execution plans, profiles, or source code.
• Hands-on experience developing AI agents, AI-assisted applications, or intelligent automation workflows, including model integration, tool use, evaluation, and production improvement.
• Experience owning critical customer issues or production incidents and coordinating resolution across teams.
• Strong customer communication, technical judgment, ownership, and written and spoken English.

Preferred Qualifications

• Experience with TiDB or another distributed SQL database.
• Experience with Kubernetes and public cloud platforms such as AWS, Google Cloud, or Azure.
• Experience building production-grade diagnostic platforms, AI support systems, or agent-driven engineering workflows.
• Experience supporting strategic enterprise customers or business-critical workloads.