Principal Site Reliability Engineer in Durham, North Carolina, United States, responsible for deploying and supporting distributed, multi-tier systems at scale to ensure high availability and fault tolerance across environments. Build and operate resilient platforms on AWS (EC2, S3, and Auto Scaling Groups) for dynamic resource management. Design, develop, and execute performance tests using Java-based frameworks such as JMeter, k6, and Rush-hour to validate system behavior under typical traffic. Define and implement observability practices to monitor system health, latency, and error rates through metrics, logs, and distributed tracing using Datadog, Grafana, Splunk, and the ELK stack. Automate operational workflows with Python and shell scripting to improve efficiency and reduce manual tasks. Support consistent build, deployment, and orchestration processes using CI/CD pipelines and Kubernetes. Establish Service Level Objectives (SLOs), Service Level Indicators (SLIs), and error budgets, and implement proactive monitoring and incident response strategies. Develop methodologies for performance, load, stress, and chaos testing and deliver analytics and reports aligned with business needs to improve resilience and optimization. Primary responsibilities include defining enterprise reliability strategies, architecting resilient systems and infrastructure, publishing performance-test results with recommendations, maintaining scalability and resiliency of complex environments, advancing observability practices at scale, mentoring junior engineers, and conducting independent tech

Principal Site Reliability Engineer in Durham, North Carolina, United States, responsible for deploying and supporting distributed, multi-tier systems at scale to ensure high availability and fault tolerance across environments. Build and operate resilient platforms on AWS (EC2, S3, and Auto Scaling Groups) for dynamic resource management. Design, develop, and execute performance tests using Java-based frameworks such as JMeter, k6, and Rush-hour to validate system behavior under typical traffic. Define and implement observability practices to monitor system health, latency, and error rates through metrics, logs, and distributed tracing using Datadog, Grafana, Splunk, and the ELK stack. Automate operational workflows with Python and shell scripting to improve efficiency and reduce manual tasks. Support consistent build, deployment, and orchestration processes using CI/CD pipelines and Kubernetes. Establish Service Level Objectives (SLOs), Service Level Indicators (SLIs), and error budgets, and implement proactive monitoring and incident response strategies. Develop methodologies for performance, load, stress, and chaos testing and deliver analytics and reports aligned with business needs to improve resilience and optimization. Primary responsibilities include defining enterprise reliability strategies, architecting resilient systems and infrastructure, publishing performance-test results with recommendations, maintaining scalability and resiliency of complex environments, advancing observability practices at scale, mentoring junior engineers, and conducting independent tech