Site Reliability Engineer (SRE)

Infobell It Solutions; Hyderabad; On-site; INR 2,800,000 - 4,500,000; Full time

Job summary

Infobell IT Solutions in Hyderabad seeks a Site Reliability Engineer (SRE) with 6-8 years of experience to ensure reliability, availability, scalability, and performance of mission-critical applications and infrastructure on GCP and Kubernetes.

You will build observability, manage SLI/SLOs, automate with Terraform/Ansible, and own CI/CD pipelines using GitHub Actions, GitLab CI/CD, Jenkins, or similar tools, collaborating with Dev and Platform teams.

Qualifications

• 6–8 years of experience in SRE/DevOps/Platform Engineering.
• Strong proficiency with Google Cloud Platform (GCP) and Kubernetes (GKE preferred).
• Experience with observability tooling such as Prometheus, Grafana, Datadog, Splunk, New Relic.
• Proficiency in Python, Go, or Java and scripting with Bash.
• Strong Linux administration and networking fundamentals.
• Experience with infrastructure as code (Terraform, Ansible) and CI/CD pipelines.

Responsibilities

• Design, maintain, and optimize highly available and scalable production systems.
• Define and manage SLIs, SLOs, and Error Budgets to improve service reliability.
• Build and enhance observability solutions using Prometheus, Grafana, Datadog, Splunk, New Relic, and related tools.
• Lead incident response, RCA, and post-mortem activities.
• Manage cloud-native apps on GCP, including GKE/Kubernetes and Docker environments.
• Develop automation and IaC solutions using Terraform and Ansible.

Skills

SRE/DevOps

GCP

Kubernetes/GKE

Observability

CI/CD

Terraform/Ansible

Automation

Incident management

Python/Go/Java

Linux/Networking

Education

Google Professional Cloud Engineer

CKA/CKAD

Terraform Associate

Tools

Prometheus

Grafana

Datadog

Splunk

New Relic

Checkly

Anodot

Coralogix

GitHub Actions

GitLab CI/CD

Jenkins

Terraform

Ansible

Job description

Site Reliability Engineer (SRE)

Role Summary

We are looking for a Site Reliability Engineer (SRE) with 6-8 years of experience to ensure the reliability, availability, scalability, and performance of mission-critical applications and infrastructure. The ideal candidate should have strong expertise in GCP, Kubernetes, observability, automation, incident management, and DevOps practices.

Key Responsibilities

• Design, maintain, and optimize highly available and scalable production systems.
• Define and manage SLIs, SLOs, and Error Budgets to improve service reliability.
• Build and enhance observability solutions using tools such as Prometheus, Grafana, Datadog, Splunk, New Relic, Checkly, Anodot, and Coralogix.
• Lead incident response, troubleshooting, RCA, and post-mortem activities.
• Manage cloud-native applications on GCP, including GKE/Kubernetes and Docker environments.
• Develop automation and Infrastructure as Code (IaC) solutions using Terraform, Ansible, and scripting languages.
• Build and support CI/CD pipelines using GitHub Actions, GitLab CI/CD, Jenkins, or similar tools.
• Collaborate with development and platform teams to improve reliability, operational efficiency, and deployment practices.

Required Skills

• 4-8 years of experience in SRE, DevOps, Platform Engineering, or Production Operations.
• Strong hands-on experience with Google Cloud Platform (GCP) and Kubernetes (GKE preferred).
• Proficiency in Python, Go, or Java and scripting using Bash/Shell.
• Strong Linux administration and networking fundamentals (TCP/IP, DNS, HTTP/S, Load Balancing).
• Experience with observability, monitoring, distributed tracing, and OpenTelemetry.
• Expertise in Terraform, Ansible, Infrastructure as Code, and automation.
• Experience in production incident management, reliability engineering, and performance optimization.

Preferred Qualifications

• Certifications such as Google Professional Cloud Engineer, CKA, CKAD, or Terraform Associate.
• Experience supporting large-scale distributed systems and implementing SRE best practices.
• Knowledge of cloud security, capacity planning, and operational excellence.

Key Success Measures

• Improved uptime and system reliability.
• Reduced MTTR and operational toil through automation.
• Enhanced observability and proactive incident detection.
• Consistent achievement of defined SLOs and service performance targets.