Senior QA Automation Engineering

Senior QA Automation Engineer
We are seeking a skilled AI + SQE Automation Engineer to drive the next generation of quality engineering through AI-assisted testing, automation, and continuous assurance practices. The ideal candidate will combine strong functional testing and automation expertise with hands-on experience using AI tools to accelerate test design, script development, and quality reporting. This role requires a quality engineering mindset focused on risk reduction, productivity improvement, and intelligent testing throughout the SDLC.
Key Responsibilities

Analyze business requirements, user stories, APIs, and technical specifications to develop comprehensive test strategies.
Design, develop, and maintain automation frameworks for UI, API, integration, and end-to-end testing.
Leverage AI tools to generate and optimize test cases, test data, automation scripts, and test documentation.
Perform AI-assisted test impact analysis to identify affected applications, APIs, user stories, and regression scope.
Build reusable automation assets and improve test execution efficiency through AI-assisted development.
Validate data quality, business rules, controls, and compliance requirements.
Execute and support continuous testing within CI/CD pipelines.
Analyze application telemetry, logs, and production signals to identify quality risks and testing gaps.
Participate in dependency analysis across code repositories, services, APIs, and downstream applications.
Validate and govern AI-generated outputs using human-in-the-loop review practices.
Required Qualifications
Quality Engineering:

Functional Testing
Integration Testing
Regression Testing
API Testing
Risk-Based Testing
Agile/Scrum Methodology
Defect Management and Root Cause Analysis
Automation:

Selenium, Playwright, or Cypress
Cucumber BDD
TestNG/JUnit
REST Assured or equivalent API automation tools
Automation Framework Design and Maintenance
Test Data Management
AI & Copilot Skills:

GitHub Copilot
Microsoft Copilot
Prompt Engineering
AI-Assisted Test Case Generation
AI-Assisted Automation Development
AI-Driven Defect Analysis
AI-Based Regression Optimization
Human-in-the-Loop Validation
Responsible AI Practices
Technical Skills:

Java, JavaScript, or Python
SQL and Data Validation
Git/Bitbucket
Jenkins, GitHub Actions, Azure DevOps
API Testing Tools
Log Analysis and Monitoring Tools
Agile tools (Jira)
DevOps
Preferred Qualifications

Test Impact Analysis
Dependency Graph Analysis
AI-Powered Test Maintenance
Self-Healing Automation Frameworks
Observability and Telemetry Analysis
OpenTelemetry, Splunk, or equivalent monitoring platforms
LLM and Agent-Based Testing
Cloud and Container Fundamentals
Kubernetes and DevOps Concepts
Data Quality Validation and Governance