Sr. Automation Tester; Airline Domain & AI

Role will be part of our Quality Engineering & Assurance (QE&A) Practice. With more than 650 clients across industry verticals and a global footprint, Cognizant QE&A practice is a recognized thought leader in quality engineer and Assurance .As enterprises simplify, modernize and secure their legacy environments for the digital era, robust quality Engineering and assurance is essential. Quality takes an end-to-end connotation and must straddle both legacy and digital systems.

Cognizant QE&A is reimagining QE&A, employing an end-to-end ecosystem approach with intelligent and automated QA processes. In so doing, increasing quality and speed to promote faster business and technology change, as well as a better customer experience.

• Design, build, and maintain scalable automation frameworks across API, UI, and mobile layers of airline applications.
• Own end-to-end test planning, execution, and defect triage across functional, regression, and integration cycles.
• Integrate automation suites into CI/CD pipelines for continuous testing and fast release feedback.

• Use AI Test Generation Tools to auto-generate, prioritize, and maintain test cases/scripts from requirements and production logs, reducing manual authoring effort.
• Apply AI Assurance practices to validate the accuracy, bias, and reliability of AI/GenAI-driven features (chat assistants, recommendation engines, dynamic pricing).
• Conduct GenAI Testing of model-backed features — prompt/response validation, hallucination checks, and output regression across releases.
• Perform AI Impediment Detection to proactively flag model drift, degraded performance, data quality issues, or automation flakiness that could block release readiness.
• Evaluate and tune AI-generated test artifacts against human-authored baselines to close coverage gaps.

• Apply airline industry knowledge (PSS, GDS, NDC, reservations, ticketing, check-in, baggage, loyalty, crew/ops) to design realistic, high-value test scenarios.
• Validate airline-specific business rules, fare/schedule logic, and regulatory compliance requirements through automated and AI-assisted checks.

Build and configure lightweight AI agents/copilots to automate repetitive QA tasks — test data generation, log triage, defect classification, self-healing locators, and result summarization