Validation QA

Role: Validation QA Location: Cupertino, CA -onsiteKey ResponsibilitiesManual Validation - 80% Perform end-to-end manual validation of workflows, data pipelines, system outputs, and UI/functional components. Develop and execute detailed validation test cases, scenarios, and checklists. Identify, document, and track defects, inconsistencies, and process deviations. Validate business rules, data integrity, configurations, and system behavior across releases. Collaborate with cross-functional teams (Product, Engineering, Data, QA) to ensure smooth issue resolution. Participate in requirement reviews and help refine acceptance criteria. Maintain detailed documentation of validation results, reports, and traceability matrices. Python Automation & AI Tooling - 20% Build lightweight Python automation scripts to reduce repetitive validation activities. Create intelligent AI-driven tools or utilities (e.g., anomaly detectors, auto-log analyzers, data validators, UI diff tools). Automate data comparisons, report generation, or test workflows where applicable. Optimize existing scripts and contribute to continuous improvement of automation frameworks. Explore AI/ML libraries to integrate smart validation approaches (e.g., pattern detection, rule-based bots). Required Skills & ExperienceValidation (Manual) Strong understanding of manual testing/validation methodologies. Experience validating data pipelines, APIs, workflows, or software modules. Ability to analyze complex business rules and edge cases. Proficiency in documenting validation artifacts (test cases, logs, bug reports). Python & Automation Hands-on experience writing Python scripts, automation utilities, or mini-tools. Familiarity with libraries such as Pandas, Requests, JSON, OpenPyXL, etc. Ability to integrate simple ML/AI components using scikit-learn, spaCy, TensorFlow, or transformers (basic level). General Strong problem-solving and analytical mindset. Ability to work independently on validation tasks while identifying automation opportunities. Good communication and documentation skills. Preferred Qualifications Experience with AI-assisted validation, anomaly detection, or rule-based automation systems. Exposure to CI/CD, basic DevOps workflows, or code versioning (Git). Knowledge of software development life cycle (SDLC) and QA processes.

Created: 2026-03-10