Site Reliability Engineer
J
JobgetherCloud infrastructure and AI
Based in the United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- At least 6 years of hands-on experience in Site Reliability Engineering, DevOps, or Platform Engineering in production environments at scale.
- Required Skills
- AWSDockerPythonKubernetesCI/CDTerraform
Requirements
- At least 6 years of hands-on SRE, DevOps, or platform engineering experience in scaled production environments.
- Deep AWS expertise, including ALB, ECS/Fargate, RDS Aurora, Lambda, and IAM.
- Production-level Python backend experience, including debugging and optimizing containerized and serverless services.
- Experience establishing or building an SRE program from the ground up.
- Practical experience with incident response, on-call rotations, root-cause analysis, postmortems, and SLOs.
- Knowledge of observability systems, including metrics, logging, distributed tracing, monitoring, and alerting.
- Understanding of Docker and Kubernetes.
- Experience with infrastructure-as-code tools such as Terraform, CloudFormation, or Pulumi.
- Hands-on experience with CI/CD pipelines, deployment automation, and release strategies.
- Proficiency in Python, Bash, or Go scripting and Linux/Unix administration.
- Experience with Git, collaborative development workflows, and infrastructure automation patterns.
- Availability for the required 24/7 P0 on-call rotation and daily overlap with client business hours.
Responsibilities
- Design and maintain observability systems for metrics, logs, traces, alerting, and monitoring.
- Define and maintain SLOs, SLAs, and error budgets for backend services.
- Participate in the 24/7 P0 on-call rotation, validate AI-generated incident reports, and escalate them to platform teams.
- Troubleshoot production incidents, perform root-cause analysis, contribute to postmortems, and implement corrective actions.
- Maintain and improve AWS production infrastructure, including ALB, ECS/Fargate, RDS Aurora, Lambda, and IAM.
- Debug and optimize Python services running in containerized and serverless environments.
- Develop self-healing mechanisms and operational automation to reduce manual work.
- Analyze observability data, forecast capacity, optimize resource use, and improve performance.
- Review infrastructure changes and improve infrastructure-as-code, CI/CD pipelines, deployment automation, and release strategies.
- Document operational procedures and mentor SRE engineers.
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