Senior Quality Assurance Automation Engineer

We are looking for a Senior Test Automation Engineer to build a practical, scalable quality strategy for a complex ERP and financial workflows product. This role is focused on end-to-end automation, API validation, batch-process verification, and data integrity checks across UI, API, and database layers. AI is expected to be used as a force multiplier for test design, log analysis, defect reporting, and automation acceleration, but the core requirement is strong engineering judgment applied to real automation bottlenecks. What You’ll Do Build and maintain robust end-to-end automation in Playwright for critical ERP and financial user journeys such as transaction flows, dashboards, and document handling.Design API automation for request and response validation, schema checks, error handling, rate limiting, and integration coverage.Create automation for source-to-target data validation, accounting integrity checks, schema verification, row-count comparison, and reconciliation across database, API, and UI layers.Automate verification of scheduled jobs, asynchronous processes, retries, output artifacts, and process-log validation.Build reusable approaches for database migration checks, ETL-style validation, and large-scale table comparison.Integrate automation into CI/CD pipelines and improve release confidence with faster feedback loops and better risk-focused coverage.Use LLM tools pragmatically for test-case drafting, automation acceleration, log summarization, bug-report generation, and edge-case discovery with human review. What You Bring 5+ years of QA or Test Automation experience, with ownership of automation strategy or framework design.Strong Playwright or similar modern UI automation experience, including selectors, waits, uploads/downloads, parallel execution, and flaky-test reduction.Strong API and microservices testing experience, including integration and negative-path validation.Strong SQL and practical experience validating data consistency, reconciliation, migration outcomes, or multi-system correctness.Ability to use Python or similar scripting for log parsing, orchestration, comparison logic, validation utilities, and reporting.Experience testing complex ERP, Fintech, banking, or other data-heavy systems with batch processes and business-rule complexity.Experience integrating automation into CI/CD and improving runtime, reliability, and feedback speed.Practical use of AI tools in QA workflows, such as generating initial test cases, summarizing logs or failures, and improving defect reports. Nice to Have Experience with visual regression or visual AI tools such as Applitools or Argos.Experience with migration validation, ETL-style testing, or large-scale data comparison frameworks.Experience with JMeter, Postman collections, or custom traffic-simulation scripts.Experience with predictive QA, risk-based prioritization, or test impact analysis.Exposure to AI-native QA tooling such as Keploy or self-healing automation frameworks.