Site Reliability Engineer

Roles & Responsibilities:

• Ensure production reliability and performance by monitoring service availability, latency, capacity, and overall system health while managing SLOs, SLIs, and error budgets.


• Automate operational processes and reduce toil by developing tools and scripts for deployment, infrastructure management, incident response, capacity planning, and other repetitive operational tasks.


• Manage incident response and root-cause analysis, participate in on-call rotations, troubleshoot production issues, and conduct blameless postmortems to implement long-term corrective actions.


• Design and improve scalable infrastructure by collaborating with software engineering teams on system architecture, distributed systems, reliability, scalability, and performance requirements.


• Manage cloud infrastructure and deployment processes using technologies such as Kubernetes, Terraform, Ansible, and CI/CD pipelines, including canary releases and automated deployment practices.


• Implement observability, capacity planning, and performance optimization across production systems, using monitoring and logging platforms such as Datadog or Splunk and optimizing SQL/NoSQL databases and distributed services.

Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field, or equivalent practical experience.


• 4+ years of experience in Site Reliability Engineering, DevOps, Platform Engineering, Cloud Infrastructure, or a closely related role, with strong exposure to production environments.


• Strong programming or scripting skills in at least one language such as Python, Go, Java, or C++, with the ability to develop automation tools and solve complex technical problems.


• Strong knowledge of Linux/Unix systems, networking, and distributed systems, including TCP/IP, DNS, load balancing, service reliability, and troubleshooting across distributed environments.


• Hands-on experience with cloud-native infrastructure and Infrastructure as Code, including Kubernetes, Terraform, Ansible, CI/CD, and automated deployment practices.


• Experience with observability and database technologies, including tools such as Datadog/Splunk and both relational and NoSQL databases, along with strong analytical, debugging, incident-management, and performance-tuning skills.