11 months ago
Palo Alto, CA, USASenior
Responsibilities
- Design and develop Go microservices powering the AI cloud platform.
- Build and maintain Kubernetes-based infrastructure for container orchestration and workload management.
- Implement cloud-native solutions optimized for scalability, reliability, and performance.
- Design distributed systems for high-availability AI workload processing.
- Use technologies such as Volcano, Prometheus, and service mesh solutions.
- Collaborate with DevOps and SRE teams on production reliability and monitoring.
- Contribute to code reviews, technical documentation, and engineering knowledge sharing.
- Use AI-assisted coding tools including GitHub Copilot, ChatGPT, and Cursor IDE.
Requirements
- At least 7 years of software engineering experience focused on distributed systems and cloud-native technologies.
- Strong proficiency in Go, including concurrency patterns and standard libraries.
- Familiarity with Python or other backend languages.
- Hands-on experience developing, deploying, and maintaining production Kubernetes clusters.
- Strong understanding of microservices architecture and implementation best practices.
- Experience with Docker, containerd, and container runtime optimization.
- Ability to independently design and implement complex system components.
- Strong collaboration and communication skills.
- Experience with AI-assisted coding tools.
- Preferred: familiarity with Prometheus, Grafana, Volcano, or service mesh technologies; open-source contributions to Kubernetes or the CNCF ecosystem; large-scale Kubernetes operations and troubleshooting; and knowledge of circuit breakers, service discovery, and distributed tracing.
Benefits
- Competitive salary and equity based on experience and skillset.
- Hybrid schedule with 3 days in the Palo Alto office and 2 days working from home.
- Applicants must be authorized to work in the United States without visa sponsorship.
About Zettabyte
Zettabyte builds Zetta-ERP, a SaaS and white‑label platform for private universities that manages the student and academic lifecycle end to end. It also develops software to deploy, manage, and optimize large‑scale GPU clusters for enterprises and governments, working with hardware supply-chain partners like Foxconn, Wistron, and Pegatron. Founded in 2016 and headquartered in Singapore, the company is privately held and serves higher‑education institutions globally.