Senior Software Engineer (Cloud Platform)

• This is not a standard control-plane platform role. You will work across both the cloud platform and database runtime, building cloud-and-engine integrated systems around Vector Lakebase so AI workloads can be scheduled faster, run more reliably, and serve real customers more efficiently
• 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

Benefits

• Equity
• Regular bonus and equity refresh opportunities
• Comprehensive medical, dental, and vision insurance
• Paid time off, including vacation, bereavement, and sick days
• Generous 401(k) and regional retirement plans
• Hybrid work model/Remote work opportunities available

• 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
• Familiarity with infrastructure automation and cloud operations tooling such as Terraform, Helm, Argo CD, Prometheus, Grafana, CI/CD systems, or similar tools
• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience
• 3+ years of experience building production systems such as large-scale SaaS platforms, data platforms, AI applications, microservices, or cloud infrastructure
• Understanding of distributed databases or database engine internals is a strong plus, especially around scalability, performance, reliability, and multi-tenant isolation
• Strong hands-on experience with Kubernetes, Docker, and at least one major cloud platform such as AWS, GCP, or Azure
• Experience building cloud-native platform systems is a strong plus, including scheduling, orchestration, deployment, configuration, upgrades, lifecycle management, or resource management