Design and build the cloud platform behind Zilliz Cloud and Vector Lakebase, bringing together cloud control plane, database runtime, scheduling, resource management, deployment, and lifecycle management to support fast workload placement, elastic scaling, multi-tenant isolation, and cost-efficient execution
Build cloud-native systems that make distributed database provisioning, scaling, upgrades, recovery, and workload migration automated, observable, rollback-safe, and efficient
Work deep across Kubernetes, multi-cloud infrastructure, networking, storage, and database engine runtimes to deliver a tightly integrated cloud-and-engine product experience
Improve platform scalability, reliability, performance, and operational simplicity as we grow across customers, regions, tenants, datasets, and AI workloads
Partner with database, reliability, and product engineers to bring new Vector Lakebase capabilities into cloud production safely and quickly
Use AI deeply across the platform engineering workflow, including deployment validation, diagnosis, incident analysis, capacity planning, documentation, code generation, and operational tooling
任职要求
3+ years of experience building production systems such as large-scale SaaS platforms, data platforms, AI applications, microservices, or cloud infrastructure
Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience
Strong hands-on experience with Kubernetes, Docker, and at least one major cloud platform such as AWS, GCP, or Azure
Familiarity with infrastructure automation and cloud operations tooling such as Terraform, Helm, Argo CD, Prometheus, Grafana, CI/CD systems, or similar tools
Experience building cloud-native platform systems is a strong plus, including scheduling, orchestration, deployment, configuration, upgrades, lifecycle management, or resource management
Understanding of distributed databases or database engine internals is a strong plus, especially around scalability, performance, reliability, and multi-tenant isolation
Strong interest in AI-assisted development and engineering productivity. We value engineers who actively use AI to multiply their output across coding, debugging, testing, documentation, and operations
