Published 1 month ago
We are looking for an experienced Operation Engineer to manage, maintain, and optimize our cloud-native infrastructure, AI-related services, and database systems. The successful candidate will collaborate with cross-functional teams to ensure the high availability, stability, and performance of our online services.
Job Description:
· Deploy, operate, monitor, and troubleshoot Kubernetes clusters and containerized workloads.
· Develop automation scripts and internal tools using Python, Java, or Go to reduce manual workload.
· Manage and maintain databases, including routine maintenance, performance tuning, backup, recovery, and fault resolution.
· Build and maintain observability systems for log collection, metrics monitoring, and performance tracking.
· Collaborate with development teams to optimize CI/CD workflows and improve delivery efficiency.
· Perform daily system checks, incident handling, and root cause analysis.
· Complexity of Cloud-Native Infrastructure: Managing and troubleshooting Kubernetes clusters and containerized workloads is inherently complex, requiring constant vigilance to ensure stability in production environments.
· Maintaining Observability: Building and maintaining systems for log collection, metrics monitoring, and performance tracking across a distributed environment is a significant ongoing technical task.
· Database Management: Beyond just maintenance, the role involves complex performance tuning, backups, and recovery, which are critical to data integrity and system availability.
· Optimizing CI/CD Workflows: Balancing the need for rapid software delivery with stability is a core DevOps challenge. The engineer must collaborate with development teams to ensure pipelines are efficient, reliable, and do not introduce errors into production.
· Skill Breadth & Adaptation: The need to maintain AI/ML infrastructure alongside traditional databases and cloud services requires a broad, high-level technical skillset and the ability to stay updated with rapidly evolving technology.
· Root Cause Analysis: Moving beyond "patching" issues to performing deep root cause analysis (RCA) is required to implement long-term optimization plans rather than just treating symptoms.
Requirement:
· Strong experience in DevOps, system operations, or cloud-native environments.
· Hands-on experience deploying, managing, and troubleshooting Kubernetes clusters.
· Proficiency in at least one programming language: Python, Java, or Go.
· Experience operating or maintaining AI/ML systems and related infrastructure.
· Fluent Mandarin for daily communication and strong English for documentation.
· Good understanding of Linux, networking, and cloud-native architecture.
· Strong problem-solving and troubleshooting skills.
· Experience with OpenSearch, Grafana, ELK Stack, APM tools, and the Argo ecosystem are preferred
The Package: