Zilliz is building the next generation of data infrastructure for AI. Founded in 2017 by the creators of Milvus, one of the world's most popular open-source vector databases, we help developers and enterprises build, deploy, and scale AI-powered applications, from semantic search and RAG to emerging agentic AI workloads.
Backed by $113 million in funding from leading global investors, Zilliz has established a strong presence in the AI infrastructure market. Milvus has earned over 46,000 GitHub stars, and our technology has reached more than 10,000 enterprise users worldwide. Companies including OpenEvidence, Exa, and Filevine rely on Zilliz Cloud to power their AI applications.
Building on our roots in vector database technology, we're expanding Zilliz Cloud into a broader AI data platform with Zilliz Vector Lakebase. As AI continues to reshape how applications are built and how data is used, we're focused on making the underlying infrastructure more powerful, scalable, and accessible to organizations worldwide.
We're entering our next phase of 10x growth: more customers, larger datasets, more complex AI workloads, and higher expectations for reliability, performance, and cost efficiency. You'll join a small, fast-moving Cloud Platform team building the core platform capabilities that run Zilliz Cloud at scale across multi-cloud environments.
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
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
High ownership: You own platform outcomes end-to-end, from design to production behavior, not just a narrow slice of the system
AI-first engineering: We actively use AI to improve coding, testing, documentation, diagnosis, and operations, but human engineering taste still matters most
Fast and focused: We ship often while keeping a high bar. This team suits engineers who want speed, autonomy, and a steep growth curve
Global collaboration: We work closely with engineering teams across regions, designing collaboration around timezone coverage to support customers globally
Competitive compensation (cash + equity)
Regular bonus and equity refresh opportunities
Medical, dental, and vision insurance
Paid time off, including vacation, sick leave, and global reset/wellbeing days
Generous 401(k) and regional retirement plans
