Core Responsibilities

• Monitoring: Monitor service health, dashboards, alerts, and key reliability indicators for assigned applications and platforms.
• Incident Response: Respond to alerts, support bridge calls, gather evidence, execute runbooks, communicate status, and escalate when required.
• Observability Support: Create and maintain dashboards, log queries, telemetry checks, alert validation, and actionable monitoring signals.
• Runbook Management: Document operational procedures, update recovery steps, validate readiness with service owners, and support knowledge sharing.
• Automation: Create scripts for repetitive checks, data collection, remediation, operational reporting, and toil reduction.
• Problem Follow-up: Support root cause analysis, postmortem documentation, and closure of assigned corrective/preventive action items.
• Continuous Improvement: Identify alert noise, toil, monitoring gaps, and preventive improvements for senior SRE review.
• SRE Alignment: Support adoption of SLOs, SLIs, SLAs, error budgets, operational readiness reviews, and production support standards.
• AI Readiness: Use or help improve AI-assisted tools for anomaly detection, incident correlation, root cause hints, and operational knowledge retrieval.
• Collaboration: Work with engineering, infrastructure, cloud, and application teams to align service performance with business goals.

Skills and Experience

• Foundations: Linux, networking fundamentals, application support, cloud fundamentals, production operations, and ITIL-style incident/change processes.
• Scripting: Python, PowerShell, Bash, or equivalent scripting for automation, diagnostics, evidence collection, and reporting.
• Tools: Git, CI/CD basics, ServiceNow or equivalent ticketing; exposure to Elastic/ELK, Grafana, Prometheus, Splunk, APM, and Azure Monitor preferred.
• Cloud & Containers: Azure services, Docker, Kubernetes, and hybrid cloud operations exposure; Terraform or infrastructure-as-code awareness preferred.
• Reliability: Basic understanding of SLIs, SLOs, SLAs, error budgets, alerting, incident response, postmortems, and operational runbooks.
• AI / AIOps Readiness: Ability to use AI-assisted investigation, anomaly detection, and correlation tools responsibly, with strong validation of evidence.
• Database: Hands-on SQL skills for operational diagnostics, data validation, and service health checks.
• Execution: Disciplined follow-through, evidence capture, documentation, escalation hygiene, and collaboration during incidents.
• Learning Mindset: Willingness to deepen skills in cloud, Kubernetes, observability, automation, resilience engineering, and secure operations.

Minimum Qualifications

• 3–7 years in production support, DevOps, infrastructure, cloud operations, or software engineering.
• Experience supporting business-critical systems and working in incident, problem, and change management processes.
• Ability to script and automate standard operational tasks using Python, PowerShell, Bash, or equivalent.
• Bachelor’s degree in computer science, engineering, or equivalent practical experience.
• Exposure to regulated enterprise, insurance, banking, or financial services environments preferred.
• Business proficiency in English; Japanese language skills are a plus.

Preferred Exposure

• Hybrid cloud platforms including on-premises and Azure-hosted services.
• Observability platforms such as ELK/Elastic, Grafana, Prometheus, Splunk, Azure Monitor, and Azure Application Insights.
• GitHub, Azure DevOps, pipelines, repositories, and operational change controls.
• Kubernetes-based production services and containerized application support.
• SRE practices including operational readiness reviews, service health reviews, and toil reduction initiatives.