QA & Automation Lead - AINative

Groupe Kardol; Manhattan Beach (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

InfoCepts LLC seeks a Quality Engineer Lead to embed an AI-native, automation-first QE capability within the BI development lifecycle. You will champion agentic automation across data validation, regression engineering, and autonomous defect management to deliver faster, more reliable BI releases.

You will oversee data validation across pipelines, build reusable QA assets, and ensure observability for accuracy, integrity, and performance of BI assets.

Qualifications

• Design and implement automated test strategies across functional, non-functional, regression, and data validation scope.
• Proven experience leveraging AI agents for automated test case generation and autonomous defect validation.
• Strong automation mindset for BI and data testing, minimizing manual QA.
• Extensive experience in end-to-end validation of dashboards, reports, KPIs, and underlying data.
• Proven experience in end-to-end testing including ETL and BI testing.
• Excellent SQL and Python skills.
• Experience designing profiling rules and data reconciliations to ensure data accuracy across pipelines.
• Hands-on ability to create detailed and comprehensive test cases for data, functional, and performance testing.

Responsibilities

• Automation-First Test Planning and Execution across BI scope.
• Lead embedded QE POD within BI delivery and drive automation-first practices.
• Provide quality governance through scorecards on coverage, cycle time, and defects.

Skills

Automation testing

AI agents

BI testing

SQL

Python

Data validation

End-to-end testing

ETL testing

Test case design

Education

Bachelor's degree in computer science or related field

Tools

SQL

Python

Job description

Our client, InfoCepts LLC, is seeking the following.

Position Title: Quality Engineer Lead

Location: Manhattan Beach, CA

Purpose of the Position

The purpose of this position is to embed an AI-Native, automation-first Quality Engineering capability within the BI development lifecycle, ensuring faster, more reliable, and business-ready releases. The QA Lead will champion agentic automation across functional and non-functional data and sssBI validation, regression engineering, data reconciliation, and autonomous defect management. By integrating directly into BI delivery, this role eliminates traditional handoffs, accelerates release cycles, and provides objective quality visibility through measurable scorecards. The QA Lead will also oversee data validation across pipelines, lightweight engineering quality checks, and observability enablement to guarantee accuracy, integrity, and performance of BI assets. Through close collaboration with development and business stakeholders, the QA Lead will transform QA from a manual, reactive function into a proactive, AI-driven quality engineering practice delivering reduced cycle times, fewer post-release defects, and sustainable automation assets that enhance BI ecosystem and overall organizational success.

Key Result Areas and Activities

• Automation-First Test Planning and Execution: Design and implement automated test strategies across functional, non-functional, regression, and data validation scope. Leverage AI agents for automated test case generation, edge case identification, and autonomous defect validation.
• Process Transformation and Continuous Improvement: Lead the transition from manual QA to embedded QE POD. Establish baseline metrics (cycle time, defect leakage, automation coverage) and drive measurable improvements. Develop reusable QA assets, automation frameworks, and governance processes to sustain long-term efficiency.
• AI-Native QE Leadership: Lead embedded QE POD within BI delivery. Champion automation-first, agentic testing practices.
• Quality Governance: Provide scorecards on coverage, cycle time, and defect leakage. Maintain regular quality operating rhythm with stakeholders.

Essential Skills

• Design and implement automated test strategies across functional, non-functional, regression, and data validation scope.
• Proven experience in leveraging AI agents for automated test case generation, edge case identification, and autonomous defect validation.
• Strong automation mindset for BI and data testing, minimizing manual QA.
• Extensive experience in end-to-end validation of dashboards, reports, KPIs, and underlying data.
• Proven experience in end-to-end testing which includes ETL and BI testing
• Proficiency in SQL and python
• Good experience in designing profiling rules and reconciliations to ensure data accuracy across pipelines.
• Hands-on expertise in building regression packs and automated test scripts.
• Ability to create detailed and comprehensive test cases for data, functional, and performance testing.
• Excellent teamwork and communication skills for effective collaboration with business teams.

Qualifications

• Bachelor s degree in computer science, Information Technology or related field.
• Minimum of 8+ years of experience in a Testing/QA role, with a focus on BI and ETL testing.