Senior Software Engineer, Cloud Reliability

Job Description

Job Description

About Zilliz

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.

About the Role

We're looking for a Senior Software Engineer focused on Cloud Reliability to help scale the infrastructure behind Zilliz Cloud.

As our customer base, data volumes, and production workloads grow, we're tackling increasingly complex reliability challenges across distributed database systems, Kubernetes, and multi-cloud infrastructure.

You'll join our Cloud Platform team and work closely with database and infrastructure engineers to keep our systems reliable, performant, and efficient. The role combines hands-on production ownership with software engineering, from responding to critical incidents and diagnosing complex failures to building the tools and automation that prevent problems from recurring.

We're looking for someone who enjoys working deep in production systems, takes ownership of difficult engineering problems, and wants to have a direct impact on the reliability of a growing cloud data platform.

What you will do:

• Own production reliability. Take responsibility for the availability, stability, and operational health of Zilliz Cloud, identifying reliability risks and driving improvements as our infrastructure and customer workloads scale.
• Participate in on-call and incident response. Take part in production on-call rotations, respond to critical incidents, investigate service disruptions, coordinate with engineering teams, and drive timely mitigation and recovery to minimize customer impact.
• Troubleshoot complex distributed systems. Diagnose production issues across Kubernetes, cloud infrastructure, networking, storage, and distributed database systems. Investigate problems across multiple layers of the stack and identify their underlying causes.
• Drive root cause analysis and incident prevention. Lead or contribute to post-incident investigations, document findings, and turn recurring failures into actionable engineering improvements, whether through code changes, better tooling, operational procedures, or improvements to the underlying platform.
• Build automation and diagnostic tools. Develop software and internal tooling for log analysis, alert correlation, incident investigation, runbook automation, and remediation workflows. Reduce repetitive operational work and make production systems easier to diagnose, recover, and maintain.
• Improve observability and operational visibility. Strengthen monitoring, logging, tracing, and alerting across Zilliz Cloud. Improve visibility into latency, availability, throughput, resource utilization, and system health to enable proactive detection and faster troubleshooting.
• Improve scalability and infrastructure efficiency. Identify potential bottlenecks, capacity constraints, and reliability risks as we grow across customers, clusters, and workloads. Work on improvements that support scalable, efficient, and reliable operations.
• Strengthen deployment safety and failure recovery. Partner with Cloud Platform and database engineers to improve production readiness, deployment reliability, rollback capabilities, and recovery mechanisms. Help ensure new platform and database capabilities can be operated safely in production.
• Improve operational practices and knowledge sharing. Develop and maintain runbooks, troubleshooting guides, and operational documentation. Share production learnings across engineering teams and help make our systems easier to operate as the organization grows.

What we are looking for:

• 3+ years of experience building or operating production cloud infrastructure, distributed systems, database platforms, or large-scale online services.
• Strong software engineering skills in Go, Python, or similar languages, with experience developing production tooling, automation, or infrastructure services.
• Hands-on experience with Kubernetes, Docker, and at least one major cloud platform (AWS, GCP, or Azure).
• Solid understanding of distributed systems, including availability, scalability, performance, fault tolerance, failure recovery, and operational tradeoffs.
• Strong troubleshooting skills across Linux, networking, storage, and cloud infrastructure, with the ability to investigate complex production issues across different system layers.
• Experience supporting production services, participating in incident response, and diagnosing reliability or performance problems in live environments.
• Familiarity with modern infrastructure and observability tools such as Terraform, Helm, Argo CD, Prometheus, Grafana, and CI/CD systems.
• Strong analytical and problem-solving skills, with the ability to move from immediate incident resolution to sustainable engineering solutions.
• Ability to work independently, communicate clearly during production incidents, and collaborate effectively with engineers across teams and time zones.
• Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.

Nice to Have

• Experience with distributed databases, storage engines, search systems, or other data-intensive infrastructure.
• Experience operating large-scale, highly multi-tenant environments, including infrastructure fleets with thousands of nodes, clusters, tenants, or customer deployments.
• Experience with multi-cloud environments, service-level objectives (SLOs), capacity planning, or reliability engineering practices at scale.

How we operate:

• High ownership and autonomy. We trust engineers to take responsibility for outcomes, not just individual tasks. You'll have the opportunity to investigate problems across system boundaries, influence engineering decisions, and drive improvements through to production.
• Engineering over repetitive operations. We believe the best way to improve reliability is to make systems easier to operate. We invest in automation, reusable tooling, and engineering solutions that reduce operational overhead as we scale.
• Fast and pragmatic. We're a growing engineering team that values speed, initiative, and thoughtful execution. We move quickly while maintaining the technical discipline needed to operate critical production infrastructure.
• Globally distributed collaboration. We work closely with engineering teams across regions and time zones. Our on-call model is designed around regional timezone coverage rather than routine overnight paging, with occasional early morning or evening collaboration to support our global operations.

The salary range above reflects annual base salary only. In addition to base salary, this role is eligible for an annual variable bonus. The target bonus percentage varies by job level and will be confirmed as part of the final offer.

Benefits

• Comprehensive Health Coverage: Medical, dental, and vision insurance plans for employees and eligible family members.
• Unlimited PTO: Flexible paid time off to rest, recharge, and take care of personal needs.
• Competitive Compensation and Equity: Competitive cash compensation and long-term incentive opportunities, including stock options.
• 401(k) with Company Match: Retirement savings plan with employer matching contributions.

Zilliz is an Equal Opportunity Employer. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable law.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.