QA Test Lead / Lead QA Engineer (AI-ML)

Key Responsibilities

• Lead end-to-end QA strategy for AI/ML and data initiatives, including data validation, model verification, API testing, and UI testing as applicable.
• Define and own test plans, test scenarios, acceptance criteria, and quality gates for features across ETL/ELT pipelines, analytics layers, and ML services.
• Design, build, and maintain scalable test automation frameworks (unit, integration, regression, and end-to-end) integrated into CI/CD pipelines.
• Validate data quality (completeness, accuracy, timeliness, lineage) using profiling, reconciliation, and automated checks across sources, transformations, and consumption layers.
• Test ML systems including model inputs/outputs, feature pipelines, performance metrics, drift/decay signals, and reproducibility across environments.
• Execute non-functional testing: performance, load, reliability, scalability, and resiliency testing for data services and ML inference endpoints.
• Ensure compliance and risk mitigation by incorporating testing for security, access controls, privacy, auditability, and secure SDLC controls in collaboration with security teams.
• Drive defect lifecycle management: triage, prioritization, root-cause analysis, and corrective/preventive actions with engineering teams.
• Mentor and guide QA engineers; establish standards for documentation, reporting dashboards, and continuous quality improvement.
• Collaborate in Agile ceremonies (backlog refinement, sprint planning, demos, retrospectives) and support release readiness decisions.
• Maintain quality metrics (test coverage, defect leakage, automation ROI, cycle time) and communicate risks and status to stakeholders.
• Support production validation (smoke checks, monitoring-based verification) and contribute to incident learnings to prevent recurrence.

Basic Job Requirements

• 7–10 years of overall QA/testing experience with at least 2+ years in a lead role (Test Lead / QA Lead / Lead QA Engineer).
• Bachelor’s degree in Computer Science / Information Technology.
• Strong experience testing data platforms (ETL/ELT, data lakes/warehouses) and APIs/microservices.
• Hands-on expertise with test automation using modern frameworks (e.g., Selenium/Playwright/PyTest).
• Strong SQL skills and experience validating complex datasets, transformations, and reconciliations.
• Experience with CI/CD and integrating automated tests into pipelines (e.g., Azure DevOps).
• Working knowledge of AI/ML concepts and ability to test model workflows (training, inference, monitoring) and data/feature pipelines.
• Excellent communication and stakeholder management skills; ability to translate quality risks into actionable plans.
• Proven ability to work in Agile/Scrum delivery models.
  • Certifications (nice to have): ISTQB, Certified Agile Tester