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