via Indeed · 2 October 2026 ·4 days ago

Test Automation Manager (Airline Domain & AI)

Cognizant
London Full-time
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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.

Test Strategy \& Automation

  • Design, build, and maintain scalable automation frameworks across API, UI, and mobile layers of airline applications.

  • Own end\-to\-end Test Strategy, test planning, test design \& execution, and defect triage across functional, regression, and integration cycles.

  • Integrate automation suites into CI/CD pipelines for continuous testing and fast release feedback.
AI\-First QA \& Validation
  • 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.
AI Agent Development for QA
  • 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.

  • Collaborate with tooling and AI/ML engineering teams to embed AI agents into the QA pipeline, enabling autonomous or semi\-autonomous test execution and reporting.

  • Continuously refine agent prompts and workflows based on QA outcomes to improve accuracy and reduce false positives/negatives.
Airline Domain QA
  • 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.
Management \& Reporting:
  • Accountable for overall Test Management, Managing Risks and Issues, Escalation management

  • Present AI\-QA metrics, coverage insights, and impediment reports to stakeholders; recommend improvements to advance the AI\-First Testing roadmap.
Mandatory Skill :
  • Strong SDET background with hands\-on test automation (Selenium/Playwright, Appium, or API automation frameworks).

  • Working knowledge of REST/API testing tools and methodologies.

  • Proven, hands\-on experience with AI Test Generation Tools for authoring/maintaining and executing test assets.

  • Exposure to GenAI Testing, Experience in AI Assurance, building agentic solutions.

  • Programming proficiency in Python and/or Java for automation scripting.

  • Airline domain QA experience (PSS, NDC, reservations, baggage, loyalty, or crew/ops systems).

  • Familiarity with CI/CD tools (Jenkins, GitLab CI, Azure DevOps) and Git.

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