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熊猫简历Systems Reliability Engineer简历模板,设计感、经典、左右结构风格简历模板,支持自定义板块、自定义颜色、AI润色、技能条、荣誉墙、一键更换模板,专业AI辅助一键优化Systems Reliability Engineer简历内容,仅需5分钟即可拥有一份精美的Systems Reliability Engineer简历模板,助力你获得「高薪职位」。

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Leo Panda

Systems Reliability Engineer
SKILLS
Kubernetes
AWS
Linux
Terraform
Prometheus/Grafana
Python
EDUCATION
Texas A&M University
STEMInfrastructure Systems
Bachelor of Science in Computer Engineering
College Station, TXAug 2014 - May 2018

Focus on distributed systems, operating systems, and networked infrastructure.

装饰
Transforming expertise into professional impact.
PROFESSIONAL SUMMARY

Systems Reliability Engineer with 6+ years of experience improving uptime, incident response, and platform scalability across cloud-native production environments. Strong background in Kubernetes, AWS, Linux, observability, and automation, with proven results reducing MTTR, increasing deployment reliability, and strengthening SLO-driven operations.

PROFESSIONAL EXPERIENCE
NexaCloud Systems
Austin, TX
Cloud InfrastructureB2B SaaS
Systems Reliability Engineer
Jul 2021 - Present
KubernetesObservability
  • Led reliability improvements for a Kubernetes-based customer platform, raising monthly service availability from 99.80% to 99.95% across 120+ production microservices within one year.
  • Built automated incident response runbooks and monitoring alerts using Prometheus, Grafana, and PagerDuty, reducing mean time to resolution by 37% year over year.
  • Standardized infrastructure as code with Terraform modules and CI validation, cutting configuration drift incidents by 42% and accelerating environment provisioning from days to hours.
  • Partnered with software engineering teams to define SLOs, error budgets, and release safeguards, decreasing failed production deployments by 31% over three quarters.
VectorBridge Technology
Dallas, TX
Enterprise SoftwareManaged Services
Site Reliability Engineer
Jun 2018 - Jun 2021
LinuxAutomation
  • Supported 24x7 Linux production systems across hybrid AWS and on-prem environments, maintaining 99.9% uptime while troubleshooting infrastructure, networking, and application performance issues.
  • Automated log analysis, patching, and health checks with Python and Bash, reducing recurring manual operational tasks by 18 hours per week.
  • Implemented centralized observability dashboards and threshold tuning for critical services, lowering false-positive alert volume by 29% and improving on-call signal quality.
  • Collaborated with security and platform teams on backup validation, disaster recovery drills, and access hardening, improving audit readiness and recovery execution consistency.

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