Senior AI Test Automation Engineer

About the role

We are seeking a highly skilled and self-motivated Senior AI Test Automation Engineer to join our Quality Engineering team. The ideal candidate will have extensive experience in test automation, database validation, AI-assisted testing, and modern quality engineering practices. This role requires expertise in building scalable automation frameworks, validating complex data migrations, and leveraging AI-enabled tools to improve productivity, accelerate testing cycles, enhance test coverage, and continuously improve software quality.

The successful candidate will play a key role in driving AI-powered quality engineering practices, championing innovation, and ensuring the effective use of AI technologies while maintaining high standards of quality, security, compliance, and reliability.

• Design, develop, and maintain scalable automation frameworks using Java, Python, and Playwright.
• Develop and execute automated functional, regression, integration, API, and end-to-end test suites.
• Perform comprehensive database testing, including data validation, data integrity, data consistency, and backend verification.
• Write and optimize complex SQL queries involving joins, subqueries, Common Table Expressions (CTEs), window functions, aggregates, and stored procedures to validate business rules and application data.
• Validate database transactions, triggers, stored procedures, views, functions, indexes, and constraints.
• Perform end-to-end validation of data across multiple databases and systems to ensure consistency and integrity.
• Validate ETL processes and data migration activities, ensuring accurate transformation, reconciliation, and completeness of migrated data.
• Perform source-to-target data validation for large-scale migration and integration projects.
• Create reusable SQL validation scripts to support automation and regression testing.
• Analyze database performance and identify data-related issues impacting application functionality.
• Validate data generated through APIs, batch jobs, scheduled processes, and background services.
• Perform backend testing by validating application data against business requirements.
• Execute performance, load, stress, security, and accessibility testing.
• Work with Snowflake to validate data, execute queries, verify data pipelines, and support reporting validation.
• Develop reusable automation utilities and testing libraries.
• Integrate automated tests into CI/CD pipelines to support continuous integration and continuous delivery.
• Utilize AI-assisted tools such as Microsoft Copilot, ChatGPT, Claude, Cursor, Git Hub Copilot, and similar technologies to accelerate test design, automation development, defect analysis, SQL generation, troubleshooting, documentation, and productivity improvements.
• Leverage Generative AI solutions to create, optimize, and maintain test scenarios, test cases, test data, validation scripts, and quality engineering documentation.
• Evaluate, recommend, and adopt emerging AI-enabled testing capabilities that improve efficiency, coverage, risk detection, and release confidence.
• Validate and review AI-generated outputs to ensure accuracy, reliability, compliance, and alignment with business requirements.
• Contribute to AI testing standards, best practices, governance, and responsible use of AI within the Quality Engineering organization.
• Collaborate closely with developers, business analysts, Dev Ops, product teams, and business stakeholders throughout the software development lifecycle.
• Analyze application logs, troubleshoot defects, perform root cause analysis, and continuously improve test coverage.
• Create and maintain test strategies, test plans, test cases, automation scripts, SQL validation scripts, and technical documentation.
• Mentor junior team members on automation best practices, AI-assisted testing approaches, and quality engineering standards.
• Drive continuous improvement initiatives that leverage AI to improve software quality, delivery speed, and operational efficiency.

• Experience with enterprise applications, microservices, and distributed architectures.
• Experience with AWS or Azure cloud platforms.
• Experience with test data management and environment management.
• Experience working with large datasets and high-volume transactional systems.
• Experience leading or supporting AI transformation initiatives within Quality Engineering teams.
• Experience establishing AI testing standards, governance practices, and adoption frameworks.
• Knowledge of AI-driven testing…