DevOps Engineer

Responsibilities

• Design, deploy and maintain backend infrastructure to ensure high availability, scalability and reliability of production systems.

• Manage cloud infrastructure on AWS and AliCloud, including performance optimization, cost management and operational excellence.

• Deploy, monitor and maintain Kubernetes clusters, distributed backend systems and supporting infrastructure services.

• Build and maintain CI/CD pipelines and infrastructure automation using GitHub Actions, Terraform and Ansible.

• Collaborate with software engineers to support backend service deployment, troubleshooting and production operations.

• Investigate production incidents, perform root cause analysis and implement preventive improvements.

• Implement infrastructure security best practices to ensure secure and reliable production environments.

• Develop internal DevOps platforms and automation tools to improve engineering productivity and operational efficiency.

• Implement monitoring, observability and alerting solutions to enhance service reliability.

• Research and integrate AI technologies into infrastructure operations, including intelligent alert analysis, ChatOps and operational automation.

Qualifications:

• 5+ years of hands-on experience in Kafka and Redis operations in large-scale production environments, be able to cooperate with developers to optimize code

• Proficient in Python / Go / Java (at least one language) and SQL programming languages

• Hands-on experience with containerization and orchestration (Docker, Kubernetes)

• Strong experience with CI/CD tools such as GitHub Actions, Ansible, Terraform etc

• At least 3 years of experience with AWS cloud platform. GCP, Azure, or Ali Cloud is a plus

• Excellent problem-solving and troubleshooting skills

• Strong team collaboration attitude and develop partnership with other teams and business

• Practical experience building or operating AIOps systems (anomaly detection, alert correlation, automated healing, or RCA)

• Familiarity with LLM-based DevOps automation (e.g., building chat-based ops assistants or AI-driven observability workflows)

• Experience using or integrating tools like Dify, Agno, or LangChain into operational workflows