Site Reliability Engineer - 1

Location: Bengaluru, India

Department: Tech

Experience: 1 - 3 years

• Design, deploy, and operate reliable and scalable systems across cloud and Kubernetes environments.

• Automate infrastructure provisioning, deployments, and operational workflows.

• Build and maintain tools for deployment, monitoring, and system operations.

• Monitor system health and performance, and proactively identify areas for improvement.

• Troubleshoot and resolve issues across development, test, and production environments.

• Participate in incident response, root cause analysis, and reliability improvements.

• Collaborate with engineering teams to improve system operability and deployment safety.

• Support and operate large-scale systems, including data-intensive or AI-driven workloads.

• 2-3 years of experience managing and operating production infrastructure and services in cloud environments such as AWS, Azure, or GCP.

• Strong hands-on experience with Linux systems in production environments.

• Experience working with containerized workloads and Kubernetes in real-world scenarios.

• Working knowledge of Infrastructure as Code tools such as Terraform, Terragrunt, or Crossplane.

• Experience designing and maintaining CI/CD pipelines using tools such as GitHub Actions, GitLab CI, Jenkins, Azure DevOps, or similar.

• Familiarity with GitOps principles and tools such as Argo CD or Flux.

• Solid understanding of cloud networking concepts, load balancing, and service connectivity.

• Experience with monitoring, logging, and alerting systems such as Prometheus, Grafana, ELK/EFK, Datadog, or equivalent.

• Proficiency in at least one scripting or programming language (e.g., Bash, Python).

• Experience working with relational databases; exposure to NoSQL or data platforms is a plus.

• Experience participating in on-call rotations, responding to production incidents, and performing root cause analysis.

• Understanding of SLIs, SLOs, and error budgets, and how they are used to guide reliability and operational decisions.

• Strong problem-solving skills and the ability to debug complex production issues.

• Good verbal and written communication skills, especially during incidents and technical discussions.

• Experience operating systems at scale or in high-availability environments.

• Exposure to on-prem or hybrid infrastructure.

• Experience supporting data platforms, analytics, or AI/ML workloads.

• A strong sense of ownership and responsibility for production systems.

• A focus on automation, reliability, and operational simplicity.

• The ability to balance speed, stability, and long-term maintainability.

• Curiosity and willingness to continuously improve systems and processes.