QA Automation Engineer
First seen by Alion on Nov 5, 2026.
Role: Senior QA Automation Engineer – Playwright with P&C insurance
Location: Piscataway, NJ (Day 1 Onsite)
Overview
As a Senior QA Automation Engineer, you will play a critical role in designing, developing, and maintaining scalable automation frameworks using Playwright. You will be responsible for integrating automated testing into CI/CD pipelines and driving shift-left quality practices across the application lifecycle. This role requires strong hands-on experience in automation engineering, test framework development, and continuous testing within Agile delivery models.
Roles & Responsibilities
Design, develop, and maintain automation frameworks using Playwright.
Create automated test scripts for functional, regression, integration, and smoke testing.
Analyze user stories and determine automation feasibility.
Integrate automation suites with CI/CD pipelines.
Execute automated test suites and troubleshoot failures.
Collaborate with Development, QA, and DevOps teams to improve product quality.
Maintain automation code repositories and testing standards.
Participate in Scrum ceremonies and provide QA automation status updates.
Publish automation execution reports, failure analysis, and improvement recommendations.
Promote best practices in automation, continuous testing, and quality engineering.
Desired Skills, Experience, Qualifications
5-8 years of experience in automation testing.
Minimum 3+ years of hands-on experience with Playwright.
Strong proficiency in TypeScript or JavaScript.
Experience building and maintaining automation frameworks.
Strong experience integrating automation into Azure DevOps, GitHub Actions, or Jenkins CI/CD pipelines.
Experience in API testing and automation.
Strong understanding of automation design patterns and testing methodologies.
Ability to analyze failures, perform root cause analysis, and improve framework stability.
Experience working in Agile/Scrum environments.
Must Have:
Design and develop robust ETL/ELT pipelines using Microsoft Fabric Data Factory and Spark Notebooks.
Integrate structured, semi-structured, and unstructured data from cloud and on-premises systems.
Implement data transformation, cleansing, validation, and orchestration processes.
Optimize data ingestion strategies for performance and reliability.