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Mei Zhang

Senior Infrastructure Engineer at Salesforce

Summary

Highly accomplished Infrastructure Engineer with 6 years of experience specializing in designing, implementing, and managing scalable and resilient cloud infrastructure. Proficient in Infrastructure as Code (IaC) principles using Terraform, automating deployment pipelines, and optimizing system performance across AWS environments. Adept at collaborating with cross-functional teams to deliver robust and cost-effective solutions that support business growth and operational efficiency.

Experience

Senior Infrastructure EngineerSalesforce
San Francisco, CAMar 2022Present
  • Led the migration of critical on-premise services to AWS, reducing operational costs by 20% and improving system uptime to 99.99%.
  • Developed and maintained IaC templates using Terraform for over 50 AWS resources, enabling automated provisioning and configuration management.
  • Implemented CI/CD pipelines with Jenkins and GitLab CI for infrastructure deployments, cutting release cycles by 30% and minimizing human error.
  • Optimized AWS resource utilization through right-sizing instances and implementing auto-scaling policies, resulting in a 15% reduction in monthly cloud spend.
  • Designed and deployed a centralized logging and monitoring solution using ELK stack and Prometheus, enhancing incident response time by 25%.
Infrastructure EngineerSlack
San Francisco, CAJul 2019Feb 2022
  • Managed and provisioned cloud infrastructure across AWS, supporting over 100 microservices for a platform with millions of daily active users.
  • Automated routine infrastructure tasks using Python and Bash scripting, saving approximately 15 hours of manual effort per week.
  • Collaborated with development teams to integrate infrastructure provisioning into application deployment workflows, reducing environment setup time by 40%.
  • Maintained and improved Kubernetes clusters for container orchestration, ensuring high availability and scalability for critical services.
  • Participated in on-call rotation to troubleshoot and resolve production incidents, achieving an average MTTR of under 30 minutes.

Projects

Education

Stanford UniversityMaster of Science in Computer Science
Stanford, CASep 2017Jun 2019
  • Thesis on 'Optimizing Container Orchestration for Cloud-Native Applications'.
  • Awarded Dean's Fellowship for academic excellence.
  • GPA: 3.9/4.0

Skills

Cloud Platforms
AWSGoogle Cloud Platform (GCP)Azure
Infrastructure as Code (IaC)
TerraformCloudFormationAnsiblePacker
CI/CD & DevOps Tools
JenkinsGitLab CIDockerKubernetesPrometheusGrafana
Scripting & Programming
PythonBashGoYAML
Operating Systems & Networking
Linux (Ubuntu, RHEL)Windows ServerVPCDNSLoad Balancing