Senior Application Support Engineer with 6+ years of experience in SaaS production support and site reliability engineering for business-critical 24x7 systems. Proven expertise in L2/L3 support, incident management, SQL …
Senior Application Support Engineer with 6+ years of experience in SaaS production support and site reliability engineering for business-critical 24x7 systems. Proven expertise in L2/L3 support, incident management, SQL troubleshooting, and root cause analysis, consistently resolving P1/P2 incidents within SLA. Strong track record of improving MTTR, system uptime (99.9%+), and operational efficiency through automation and proactive monitoring. Experienced in leveraging automation and emerging GenAI techniques to enhance incident resolution and operational intelligence.
<p>Delivered L2/L3 client-facing production support for SaaS applications serving 500+ enterprise users, maintaining 99.9%+ uptime.<br>
Supported business-critical workforce management platform ensuring uninterrupted payroll and scheduling operations for enterprise clients.<br>
Ensured uninterrupted workforce operations (payroll, scheduling) by rapidly resolving production incidents in a business-critical environment.<br>
Managed and resolved 20–30+ incidents per week, including P1/P2 critical issues, achieving ¿95% SLA compliance.<br>
Took end-to-end ownership of major incidents, reducing mean time to resolution (MTTR) by 20–25% through efficient triaging and RCA.<br>
Engineered an automation solution for recurring failures (Openfire, DB connectivity), reducing resolution time from 60 minutes to ¡1 minute.<br>
Automated operational workflows using Python and PowerShell, improving efficiency and reducing manual effort by 25%.<br>
Leveraged Claude (LLM) to automate log analysis, incident summaries, and knowledge base documentation, improving troubleshooting speed and consistency.<br>
Reduced recurring production incidents by 15–20% through proactive monitoring, alert tuning, and problem management initiatives.<br>
Troubleshot application, API, and database issues, including backend failures and data inconsistencies.<br>
Performed deep-dive troubleshooting using logs, metrics, and traces (Splunk, Grafana, Datadog), accelerating issue identification and resolution.<br>
Utilized advanced SQL queries for data validation and issue resolution, reducing data-related defects by 30%.<br>
Conducted post-incident RCA and trend analysis, implementing preventive fixes to improve system reliability.<br>
Collaborated with engineering, product, and release teams to resolve defects and ensure smooth production deployments.<br>
Monitored system performance, application health, and capacity metrics, ensuring adherence to SLA/OLA targets.<br>
Managed incident, problem, and change lifecycle via ServiceNow.<br>
Authored runbooks, SOPs, and KB articles, reducing onboarding time by 30%.<br>
Applied AIOps techniques for anomaly detection and incident trend analysis.<br>
Supported cloud-hosted distributed systems, ensuring high availability and performance.</p>
Delivered L2/L3 client-facing production support for SaaS applications serving 500+ enterprise users, maintaining 99.9%+ uptime., Supported business-critical workforce management platform ensuring uninterrupted payroll and scheduling operations for enterprise clients., Ensured uninterrupted workforce operations (payroll, scheduling) by rapidly resolving production incidents in a business-critical environment., Managed and resolved 20–30+ incidents per week, including P1/P2 critical issues, achieving >95% SLA compliance., Took end-to-end ownership of major incidents, reducing mean time to resolution (MTTR) by 20–25% through efficient triaging and RCA., Engineered an automation solution for recurring failures (Openfire, DB connectivity), reducing resolution time from 60 minutes to
<p>Handled 40–60+ customer interactions daily, maintaining high resolution accuracy.<br>
Achieved 90%+ first contact resolution (FCR).<br>
Reduced escalation rate by 15%.<br>
Ensured SLA adherence across high-volume ticket queues.</p>
Handled 40–60+ customer interactions daily, maintaining high resolution accuracy., Achieved 90%+ first contact resolution (FCR)., Reduced escalation rate by 15%., Ensured SLA adherence across high-volume ticket queues.
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