Site Reliability Engineer

Role :

Senior Site Reliability Engineer / Reliability Architect

Locations :

Pune,Bengalore,Chennai,Pune,Noida

Job Description :

Reliability Architect with over 9 years of experience in proactive monitoring, automation, and observability. Skilled in AIOps / MLOps, infrastructure management, and performance optimization using modern tools and practices. Adept at leading incident response, mentoring support teams, and driving cross-functional collaboration to ensure system reliability and scalability.

Key Responsibilities :

Monitoring and Automation

Proactively monitor software systems to prevent incidents and automate routine operational tasks.

Effective Monitoring

Design monitoring systems that trigger alerts based on symptoms rather than outages, ensuring early detection and resolution.

Application Performance Monitoring (APM)

Implement and manage APM tools like New Relic or Dynatrace to track application performance, identify bottlenecks, and optimize resource usage.

Log Analysis with Splunk

Use Splunk to analyze logs for troubleshooting, anomaly detection, and improving system reliability.

Dashboards Preparation

Build intuitive dashboards to visualize system health, performance metrics, and operational KPIs.

Alerts Setup

Configure intelligent alerts based on thresholds and anomalies to ensure timely incident response.

Reports Scheduling

Automate regular reporting to provide insights into system performance, reliability, and trends.

Reliability Metrics

Define and track metrics such as SLOs, SLIs, and error budgets to measure and maintain system reliability.

Observability Skills

Apply observability practices including distributed tracing, logging, and metrics collection to gain deep insights into system behavior.

AI-Driven Monitoring & Automation

Utilize AIOps techniques to proactively detect anomalies, automate incident response, and enable self-healing systems through intelligent alerting and predictive analytics.

Observability & ML Integration

Integrate machine learning models with observability tools to enhance system insights, optimize performance, and ensure reliability of AI-powered services in production.

Cross-Team Collaboration

Work closely with development and support teams to enhance service reliability through rigorous testing and release procedures.

Capacity Planning

Participate in system design reviews and capacity planning to ensure scalability and performance.

Debugging and Incident Response

Lead incident response efforts, analyze debugging information, and manage rollbacks of faulty software deployments.

Mentoring Support Teams

Guide and mentor L1 / L2 support teams to establish best practices in monitoring and observability.

Infrastructure Management

Manage infrastructure using tools like

Chef ,

Ansible ,

Terraform ,

GitLab CI / CD , and

Kubernetes .

Documentation

Maintain comprehensive documentation of processes and procedures to ensure operational consistency and reduce redundancy.

Proactive Mindset

Approach challenges with enthusiasm, ownership, and a continuous improvement mindset.