Role Summary

Responsible for establishing quality standards, testing strategy, release readiness, and data validation practices across the platform.

Responsibilities

- Define test strategy and quality standards
- Lead integration, regression, UAT, and release testing
- Validate migration outcomes and data reconciliation results
- Drive automation strategy
- Mentor QA resources and establish best practices

Required Skills

- Test Automation
- API Testing
- SQL Validation
- Data Reconciliation Testing
- Integration Testing
- Regression Testing
- UAT Coordination
- Release Validation
- Defect Management
- Root Cause Analysis

GenAI

- Hands-on experience with GenAI coding assistants (Claude Code, GitHub Copilot, or similar) for AI-assisted development.
- Prompt engineering skills writing explicit instructions and feedback to guide AI toward desired output.
- Ability to critically review and validate AI-generated code and content before use.
- Basic understanding of LLM concepts — RAG, context windows, hallucinations, and responsible AI practices.

Preferred Skills

- Databricks Validation Frameworks
- PySpark Testing
- Performance Testing

Banking Applications

📌 AI QA Lead Engineer (Chennai)
🏢 Platlap Solutions
📍 Chennai