Architect

1 day ago

Hyderabad, Telangana, India Birlasoft Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Area(s) of responsibility

Job Description: Reliability Architect – 6A
Reliability Architect with over 10 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.

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