System Reliability Engineer / T2 Support Engineer

About the Role

We are looking for an engineer who enjoys understanding how systems behave in real production, not just writing features. This role is responsible for maintaining reliability, stability, and smooth functioning of our live platform running on Google Cloud.

You will act as the first technical owner of production systems — monitoring services, investigating alerts, resolving issues, and performing controlled configuration and operational changes. This role works closely with backend developers, QA, and infrastructure teams to prevent incidents and reduce downtime.

This is not a call-center support role and not a pure development role — it is a hands-on technical position focused on debugging, incident handling, and system operations.

Tech Stack

• Google Cloud Platform (Compute, Logging, Monitoring)
• Java (Spring Boot based microservices)
• MongoDB
• Apache Kafka (event-driven architecture)
• Redis cache
• Linux servers

Key Responsibilities

Production Monitoring & Alert Handling

• Monitor application health, latency, errors, consumer lag, database connections, and resource utilization
• Acknowledge and investigate monitoring alerts
• Perform first-level troubleshooting and stabilize services
• Identify whether issue is infra, application, database, or messaging related

Incident Response

• Participate in on-call rotation
• Diagnose production incidents and restore services with minimal downtime
• Safely restart services, scale instances, or rollback deployments when required
• Communicate incident status to stakeholders

Technical Support & Operational Changes

• Handle technical support tickets requiring engineering understanding
• Update configurations and feature flags
• Manage scheduled jobs / cron triggers
• Trigger or replay events in Kafka
• Assist in minor Java configuration/code fixes when needed
• Coordinate production releases

Database & Messaging Operations

• Investigate MongoDB performance issues and slow queries
• Monitor and resolve Kafka consumer lag and stuck messages
• Manage Redis cache behavior (TTL, eviction, connection issues)

Logs & RCA

• Analyze logs and metrics to determine root cause of issues
• Prepare basic Root Cause Analysis (RCA) reports
• Suggest preventive actions to reduce recurring incidents