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Zilliz

Open-source vector database for AI workloads

Senior Software Engineer - Cloud Platform

Platform EngineeringConfirmed live in the last 24 hours
Full-timeRedwood City, CA, USA

About the Job

Requirements

  • At least 3 years of experience building production systems such as large-scale SaaS platforms, data platforms, AI applications, microservices, or cloud infrastructure.
  • A 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.
  • Strong interest in AI-assisted development and engineering productivity, including using AI across coding, debugging, testing, documentation, and operations.

Responsibilities

  • Design and build the cloud platform behind Zilliz Cloud and Vector Lakebase, integrating the 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 automate distributed database provisioning, scaling, upgrades, recovery, and workload migration, while making these processes observable, rollback-safe, and efficient.
  • Work across Kubernetes, multi-cloud infrastructure, networking, storage, and database engine runtimes to deliver an integrated cloud-and-engine product experience.
  • Improve platform scalability, reliability, performance, and operational simplicity as the company grows 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 across the platform engineering workflow, including deployment validation, diagnosis, incident analysis, capacity planning, documentation, code generation, and operational tooling.

Desired Qualifications

  • Experience building cloud-native platform systems, including scheduling, orchestration, deployment, configuration, upgrades, lifecycle management, or resource management.
  • Understanding of distributed databases or database engine internals, especially scalability, performance, reliability, and multi-tenant isolation.

About the Company

Zilliz

Open-source vector database for AI workloads

Zilliz builds AI data infrastructure centered on vector databases. Its flagship open-source Milvus stores and searches high-dimensional embeddings, while Zilliz Cloud offers a fully managed vector database service for enterprise AI workloads. Milvus and Zilliz Cloud organize data as vectors (including text, JSON, and geospatial information) and enable fast similarity search, retrieval, and analytics using a lake-native architecture that separates storage from compute. The company differentiates itself with open-source roots, an enterprise-ready cloud, and features like hybrid retrieval, filtering, and reranking, aimed at scalable, cost-effective AI data infrastructure for tasks such as semantic search and retrieval-augmented generation.

Company size
51-200
Company stage
Series B
Total funding
$113M
Headquarters
Redwood City, CA
Founded
2017

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