AI QA Lead Engineer

Platlap Solutions; Chennai District; On-site; INR 1,500,000 - 2,200,000; Full time

Job summary

Platlap Solutions is seeking a QA Leader to establish quality standards, define testing strategies, and oversee automation and data validation across our platform. You will mentor QA resources and drive best practices while coordinating integration, regression, UAT, and release testing to ensure smooth migrations and data reconciliation.

The role emphasizes hands-on automation, test strategy development, and collaboration with GenAI-assisted development teams to ensure high-quality software

Qualifications

• 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.

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.

Skills

Test Automation

API Testing

SQL Validation

Data Reconciliation Testing

Integration Testing

Regression Testing

UAT Coordination

Release Validation

Defect Management

Root Cause Analysis

GenAI tooling

Tools

Databricks Validation Frameworks

PySpark Testing

Performance Testing

Job description

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 clear 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

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