# 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

QA Strategy, Quality Governance, AI Testing Governance, Team Leadership, Budget Management, Risk Management, Stakeholder Management, Agile Transformation, AI Quality Gates, DeepEval, LLM Quality SLAs, OpenTelemetry, GitHub Copilot Enterprise, OWASP LLM Top 10, EU AI Act Compliance, Azure DevOps, Jira Align, Executive Reporting, OKR Framework, Lean Six Sigma, PMP, ISTQB Expert

## 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