Database AIOps Infrastructure Engineer

Role Overview

We seek a skilled AI Infrastructure Engineer to enhance the Database Autonomy Service (DAS) team. This role focuses on crafting AI-driven operations tools that enable database services to self-heal, optimize performance, and remain secure at scale. Your work will lie at the convergence of distributed databases, large-scale operational tooling, and applied artificial intelligence, pioneering autonomous database management technologies.

Key Responsibilities

• Architect, develop, and deploy features within DAS including anomaly detection, root cause analysis, system performance optimization, and security enhancements across various database engines such as PolarDB, MySQL, PostgreSQL, Redis, and MongoDB.
• Lead the transition toward AI-native DAS by researching and implementing AI Agent technologies to create autonomous operation agents that support and eventually automate routine database tasks.
• Manage the complete feature development lifecycle encompassing on-call duties, handling escalated support tickets, bug investigation, incident troubleshooting, improving user experience, and refining system performance and cost-efficiency.

Requirements

• Master's degree in Computer Science, AI, or related disciplines.
• Over two years of experience in backend engineering focusing on areas like databases, AI-driven applications, agent-based systems, or infrastructure platforms.
• Demonstrated leadership in designing and implementing significant system modules or architectural components, delivering highly reliable software products.
• Proven ability to collaborate cross-functionally with diverse teams to craft roadmaps and achieve shared objectives.

Preferred Credentials

• Extensive practical understanding of key database technologies and their operational frameworks, including monitoring, diagnostic procedures, high availability setups, and backup/recovery processes.
• Experience working with AIOps, large language model powered agents, or autonomous system deployments in live production contexts.
• Contributions to open-source projects or scholarly publications related to AI, databases, or systems engineering.