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Sample resume with fictional details. Replace the content with your own experience and qualifications. Format: Editorial.

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Priya Krishnan

QA Manager · 11 year experience

Mumbai, Maharashtra

[Your email] · [Your phone]
[Your LinkedIn URL] · [Your GitHub / Portfolio URL]

Professional Summary

  • Eleven-year veteran in software quality engineering with 3+ years in management, overseeing a 15-person QA team across fintech and digital banking products
  • Championed AI testing adoption by deploying GitHub Copilot for test generation and DeepEval for LLM feature validation across 4 product lines
  • Delivered 99.8% test coverage SLAs across digital banking products serving 2M+ users with zero critical-severity escapes in 8 consecutive production releases
  • Established company-wide AI quality governance framework integrating hallucination rate monitoring, toxicity scoring, and bias detection metrics
  • Reduced regression cycle time by 65% through AI-assisted test selection, intelligent orchestration, and parallel cloud execution
  • Led cross-functional alignment between Dev, QA, and Product teams embedding quality gates at every sprint planning and design review phase
  • Built QA hiring pipeline and onboarding curriculum that scaled the team from 6 to 15 engineers in 18 months with 90% retention rate
  • Defined comprehensive OKRs and quality KPIs including DQPI, defect escapement rate, MTTD, and AI model drift alert thresholds

Work Experience

QA Manager

[Company name] · [Start date – End date]

11 years in software quality engineering across fintech, e-commerce, and insurance domains. Led teams of up to 15 QA engineers handling functional, regression, API, performance, and AI model testing. Managed release calendars, defect SLAs, and QA tool licensing budgets of Rs. 40L annually. Partnered with engineering directors to define quarterly quality OKRs and report quality metrics to C-suite stakeholders at fortnightly leadership reviews.

Responsibilities

  • Manage and mentor a 15-person QA team spanning functional, automation, API, and AI testing disciplines
  • Define quarterly quality OKRs aligned to engineering and business objectives, reported to Director Engineering
  • Drive AI testing adoption including LLM evaluation, hallucination testing, and AI safety acceptance criteria
  • Own test strategy, risk-based testing plans, and execution governance across 4 digital banking product lines
  • Partner with product managers to embed quality acceptance criteria at sprint planning and story refinement
  • Report quality KPIs — defect escapement, MTTD, coverage metrics, AI drift alerts — to senior leadership
  • Manage QA tool stack budget including TestRail, JIRA, Playwright, and AWS test infrastructure licensing
  • Conduct performance reviews, career development plans, and quarterly feedback sessions for all team engineers
  • Oversee CI/CD quality gates, gate-failed build triage process, and hot-fix release quality sign-off
  • Champion shift-left testing and developer testing culture through pair-testing sessions and QA-dev guilds
  • Lead retrospectives and quarterly process improvement programs using Lean and Six Sigma methodologies
  • Coordinate with security, DevOps, and data teams for end-to-end coverage of OWASP and compliance requirements

Project Experience

AI-Assisted Mobile Banking Test Suite

Built an AI-powered test suite for a mobile banking app using Playwright and GitHub Copilot, reducing manual test scripting effort by 60% and achieving full API coverage. Technologies: Playwright, Python, GitHub Copilot, Azure DevOps, Appium.

LLM Feature Validation Framework

Designed acceptance criteria and validation workflows for 12 LLM-powered chatbot features using DeepEval for hallucination, toxicity, and coherence scoring integrated into CI/CD. Technologies: DeepEval, Python, LangSmith, JIRA, Gherkin.

QA Transformation Program

Spearheaded a 12-month quality transformation covering shift-left adoption, AI tool deployment, and team upskilling across 3 product lines serving enterprise fintech clients. Technologies: JIRA, TestRail, GitHub Copilot, Confluence, Agile Coaching.

Regression Optimization Initiative

Reduced nightly regression suite runtime from 4.5 hours to 95 minutes through AI-based flaky test elimination, parallel execution, and intelligent test selection algorithms. Technologies: TestNG, Selenium Grid, Python, GitHub Actions, Test Impact Analysis.

Technical Skills

Test ManagementTeam LeadershipJIRATestRailZephyr ScaleAgileSAFeSeleniumPlaywrightPythonRestAssuredGitHub ActionsAzure DevOpsAWS CloudWatchDeepEvalGitHub CopilotLLM Feature TestingQuality KPIsOKRsRisk ManagementISTQBPMP