SQE Automation Engineer (AI)

Location & Duration

Jersey City, NJ / Charlotte, NC (Onsite) – 12 months

Role Overview

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. This role requires a quality engineering mindset focused on risk reduction, productivity improvement, and intelligent testing throughout the SDLC. The ideal candidate will combine functional testing and automation expertise with experience using AI tools to accelerate test design, script development, and quality reporting.

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)

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