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This role focuses on ensuring the reliability and performance of critical systems through advanced Site Reliability Engineering practices.

Manage and maintain infrastructure across multi-cloud environments (AWS, Azure, GCP). Implement Infrastructure as Code using Terraform and Deployment Manager for automated provisioning. Develop and optimize CI/CD pipelines with tools like GitHub Actions for efficient software delivery. Containerize applications and orchestrate workloads using Docker and Kubernetes.

Automate operational tasks through Linux, Bash, and Python scripting. Monitor system health and performance using tools such as Splunk, Grafana, Dynatrace, and Datadog. Define and manage Service Level Indicators (SLIs) and Service Level Objectives (SLOs), including error budgets. Collaborate within ITSM/ITIL frameworks and utilize ticketing systems like JIRA and ServiceNow.

Handle production support, manage releases effectively, and conduct chaos engineering experiments to test system resilience. Employ tools like LitmusChaos or Gremlin for advanced resilience testing. Integrate PagerDuty or Opsgenie for automated alert escalation. Automate deployment gates based on SLO compliance and leverage predictive analytics for proactive scaling.

We are seeking professionals with 6-9 years of overall IT experience, including a minimum of 4+ years specifically in Site Reliability Engineering.

Essential expertise includes multi-cloud environments (AWS, Azure, GCP), Infrastructure as Code (Terraform, Deployment Manager), CI/CD pipelines (GitHub Actions), containerization and orchestration (Docker, Kubernetes), and scripting languages (Linux, Bash, Python).

A strong understanding of monitoring and APM tools (Splunk, Grafana, Dynatrace, Datadog) is crucial. Experience with SLIs/SLOs, error budgets, ITSM/ITIL processes, and ticketing tools (JIRA, ServiceNow) is also required. Familiarity with production support, release management, chaos engineering, and automated escalation tools is expected.