Quality Engineering Lead with 10+ years in Quality Engineering Leadership & AI-Assisted Testing
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Seasoned QA Automation Manager with 17+ years of hands-on experience building and leading high-performing QA teams across Telecom, Logistics, BFSI, Trading, and Healthcare. Translates business goals into concrete automation strategies delivering measurable outcomes - 40% reduction in regression cycles and 30% drop in defect leakage. Equally effective across people leadership and test architecture built and scaled automation frameworks using Cucumber BDD, Robot Framework, and Playwright, while integrating AI-driven tooling (GitHub Copilot, Claude Code, Playwright MCP) to achieve 2x faster test case generation. Mentors engineers across geographically distributed teams to take ownership and deliver quality independently.
Government Engineering College, Palakkad
B.Tech · Computer Science & Engineering
N/A – June 30, 2008
Mobileum
QA Manager
June 1, 2021 – Present
Bengaluru, Karnataka, India
Maersk
QA Lead
September 1, 2020 – April 1, 2021
Bengaluru, Karnataka, India
IG Infotech
QA Team Lead
September 1, 2011 – September 1, 2020
Bengaluru, Karnataka, India
IGATE Patni
System Analyst
April 1, 2008 – August 1, 2011
Bengaluru, Karnataka, India
ISTQB Certified Tester - Foundation Level (CTFL)
ISTQB
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project experience across multiple industries (Telecom, Logistics, BFSI, Trading, Healthcare) and roles (QA Manager, QA Lead, QA Team Lead, System Analyst) indicates adaptability and a broad perspective. Their experience leading geographically distributed teams and fostering team growth aligns well with a collaborative and inclusive culture. The continuous learning demonstrated by adopting new technologies like AI-assisted testing suggests a growth mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, mentoring, and stakeholder management skills. Their experience in coordinating distributed teams and standardizing processes indicates excellent operational fit. The focus on measurable outcomes (e.g., 40% reduction in regression cycles) highlights a results-oriented approach. The adoption of AI-assisted tools also shows a proactive and innovative mindset.