Ramesh Iyer
QA Director · 16 years experience
Chennai, Tamil Nadu
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Professional Summary
- Sixteen-year quality engineering leader directing a 65-person global QA organization across product engineering, cloud platforms, and AI-powered features in an enterprise SaaS company
- Transformed the QA organization from a traditional testing team to an AI-native quality center within 18 months, achieving the industry's first AI Testing Maturity Score of Level 4 in India
- Owns the company's AI Quality Governance framework mandating AI safety testing, LLM evaluation gates, and OWASP LLM Top 10 compliance for every AI feature before production deployment
- Secured $2.4M in engineering investment for AI testing tooling, cloud test infrastructure, and team upskilling programs including DeepEval, LangSmith, and Garak deployments
- Drives C-suite quality reporting with AI quality metrics dashboard covering hallucination rates, model drift indicators, defect prediction accuracy, and automation ROI metrics
- Led the company's EU AI Act compliance readiness assessment and testing program covering 14 AI-powered features across EU-regulated markets in financial services and healthcare
- Established Quality Engineering as a Platform strategy providing shared AI testing services, automation frameworks, and quality APIs to 12 product squads as internal customers
- Reduced post-release critical defects by 78% over 3 years through risk-based testing, AI defect prediction models, and enforced quality gates in the CI/CD pipeline
Technical Skills
Work Experience
QA Director
[Company name] · [Start date – End date]
16 years in quality engineering managing progressively larger organizations from QA Lead (3 engineers) to QA Director (65 engineers) across banking, insurance, and enterprise SaaS domains. Managed QA P&L of Rs. 8.5Cr annually. Reported to the VP Engineering in a 4,000-person global technology organization. Oversaw quality engineering for products generating $180M ARR across enterprise and mid-market customer segments.
Responsibilities
- Direct a 65-person global QA organization structured across 5 domain teams: functional, automation, AI quality, performance, and security testing
- Define AI quality strategy and governance framework aligned to company AI product roadmap and EU AI Act obligations
- Own AI testing governance policy: hallucination rate SLAs, safety evaluation gates, and LLM red teaming calendar
- Manage Rs. 8.5Cr annual QA budget across tooling procurement, cloud infrastructure, talent acquisition, and training
- Present quality health metrics, defect trends, AI risk assessments, and regulatory compliance status to VP Engineering and CEO
- Represent QA on company AI Ethics Committee and Enterprise Architecture Review Board for strategic decisions
- Partner with CISO on AI security testing strategy, OWASP LLM Top 10 compliance, and vulnerability disclosure
- Drive Agile transformation and quality maturity improvements using Lean principles across 12 product squads
- Lead executive talent management including QA Director and Manager hiring, succession planning, and retention
- Define 3-year quality engineering technology roadmap aligned to the company's AI-first product strategy
- Negotiate enterprise contracts with test tool vendors, cloud platform providers, and AI evaluation tool companies
- Chair quarterly QA Community of Practice for knowledge sharing, innovation showcasing, and cross-team alignment
Project Experience
AI Quality Governance Framework
Built the company's AI quality governance framework mandating DeepEval-based acceptance criteria, OWASP LLM Top 10 security gates, and AI ethics review checklists for all 14 AI-powered product features. Technologies: DeepEval, RAGAS, LangSmith, OWASP LLM Top 10, Governance Workflow Automation.
EU AI Act Compliance Testing Program
Led the company's EU AI Act readiness assessment across 14 AI features, defining test coverage for high-risk AI obligations covering transparency, data quality validation, human oversight verification, and bias detection. Technologies: Risk Assessment Frameworks, DeepEval, RAGAS, Compliance Dashboards, Explainability Testing.
Quality Engineering Platform
Transformed QA from a project-based team to a platform model providing shared automation frameworks, AI evaluation APIs, and testing infrastructure to 12 product squads with SLA-backed service delivery. Technologies: GitHub Actions, API Gateway, DeepEval, Playwright, OpenTelemetry, Service Catalog.
AI Defect Prediction System
Deployed ML-based defect prediction models in the CI pipeline using historical defect data, code change patterns, and test coverage metrics, reducing critical defect escapes to production by 78% over 3 years. Technologies: Python, Scikit-learn, JIRA API, GitHub Actions, OpenTelemetry, MLflow.
Education
M.Tech Software Engineering – IIT Madras, 2008; B.Tech CSE – Anna University, 2006; Executive Leadership Program – IIM Chennai, 2019
Certifications
ISTQB Expert Level – Advanced Test Manager (CTEL-ATT); PMP – Project Management Professional; Lean Six Sigma Black Belt; AWS Solutions Architect Professional; Certified SAFe Program Consultant (SPC6); GitHub Copilot Enterprise Administrator
Achievements
Named India's Top 25 QA Leaders by Software Testing Planet 2024; Reduced critical production defects by 78% in 3 years; Quality Engineering Platform adopted by all 12 product squads; Secured $2.4M AI testing investment approval; First Indian SaaS company to achieve Level 4 AI Testing Maturity Score; Invited board member for AI Ethics Committee