Posted 14 June, 2026
Sr Project Lead-App Development
Birlasoft
Hyderabad,INDI,IN
Full Time
Reference: 118_656062_54957644
Area(s) of responsibility
Job Description: Reliability Sr. Tech Lead/Architect - 5B
Reliability Architect with 8 to 12 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.