Cofounder, Senior QA Automation Engineer - AI-Native Analytics Platform (**Equity-Based)

SQOR.ai has reimagined Business Intelligence by building an AI-native Decision Intelligence platform that analyzes operational data directly from the systems companies already use. The Senior QA Automation Engineer will build and own the automated testing infrastructure for the platform, ensuring stability and reliability as it scales across industries.

Responsibilities:

• QA Automation Architecture: Design and build the automated testing framework that validates our application, APIs, and analytical services
• Application Testing: Create automated tests for the web application and backend services to ensure features function correctly across releases
• AI Output Validation: Develop testing approaches that verify the reliability and consistency of AI-generated insights, recommendations, and analytical outputs
• Data Ingestion Testing: Validate data ingestion pipelines from SaaS tools and databases to ensure accurate extraction and transformation
• KPI and Analytics Validation: Confirm that generated KPIs, analytical results, and causal analysis outputs remain accurate across datasets
• CI/CD Integration: Integrate automated testing into the deployment pipeline so that releases are validated automatically before production
• Performance Testing: Evaluate system performance under heavy workloads including large datasets and concurrent user activity
• Regression Testing: Build automated regression tests that ensure new features do not break existing functionality
• Engineering Collaboration: Work closely with developers and data engineers to diagnose issues and improve system reliability
• Quality Standards: Establish QA practices and testing methodologies that scale with the company

Requirements:

• Strong experience building QA automation frameworks for SaaS platforms
• Hands-on experience with tools such as Playwright, Cypress, Selenium, or similar automation frameworks
• Strong programming ability in Python or JavaScript for building automated tests
• Experience testing APIs, backend services, and distributed systems
• Familiarity with data pipelines or analytics platforms where data accuracy matters
• Understanding of challenges involved in testing AI or machine learning outputs
• Experience integrating tests into CI/CD pipelines such as GitHub Actions, GitLab, or Jenkins
• Ability to diagnose issues across the UI, backend services, and data layer
• Strong communication skills and ability to collaborate with engineers and product leadership
• Extremely detail oriented and committed to building reliable software