Quality Engineer, Senior

NJM Insurance Group•Trenton, NJ

1d•$100,402 - $116,574

About The Position

As a Senior Quality Engineer, you will be responsible for functional and automation testing of NJM’s business applications. The role actively uses Generative AI and AI-assisted engineering tools to enhance test design, automation development, defect analysis, test data generation, and software quality delivery. The successful candidate combines quality engineering expertise with AI-enabled productivity and automation capabilities. You will work in an agile, small-team environment focused on speed and quality, contributing to test planning and comprehensive test strategies. You will develop and maintain reusable automated tests, perform manual and automated testing, validate backend systems and APIs, and collaborate with cross-functional teams to support quality objectives and incremental business value. You will also integrate AI-enabled tools and workflows into quality engineering processes to improve productivity, reduce manual effort, and increase delivery velocity. The role requires 7+ years of experience in software delivery, including 5+ years in quality engineering, QA, software testing, or test automation, and a bachelor’s degree in computer science or equivalent. Compensation is commensurate with experience and credentials, with a stated pay range of $100,402–$116,574. Eligible full-time employees receive a competitive Total Rewards package.

Requirements

7+ years of experience in software delivery, including 5+ years in Quality Engineering, QA, software testing, or test automation.
Bachelor’s degree in computer science or equivalent.
Software engineering experience with hands-on coding proficiency in a language such as Java, Python, C#, or JavaScript.
Proven experience building and driving an automation-first testing strategy, with the ability to implement automated solutions across the software delivery life cycle.
Demonstrated experience using Generative AI and AI-assisted engineering tools to improve software testing and quality engineering outcomes.
Strong experience with test automation frameworks such as Selenium, Playwright, Cypress, or similar tools.
Strong expertise in SQL, API testing, and backend/system validation.
Hands-on experience with AI-enabled tools such as GitHub Copilot, ChatGPT, Claude, or similar platforms to accelerate test design, test automation development, test data creation, and defect analysis.
Experience working in Agile development environments.
Strong written and verbal communication skills with technical and non-technical audiences.

Nice To Haves

Experience in the P&C insurance domain.
Experience with the Guidewire Insurance Suite.
Experience implementing AI-assisted test automation solutions and intelligent test generation techniques.

Responsibilities

Work in an agile, small-team environment focused on speed and quality.
Contribute to test planning and comprehensive test strategies using appropriate testing techniques.
Design, develop, and maintain complex, reusable test automation scripts to support faster regression and delivery cycles.
Collaborate with cross-functional teams to align on quality objectives, requirements, and incremental business value.
Perform manual and automated testing against software requirements, risk assessments, and quality standards.
Perform backend validation and web service and API testing using appropriate tools.
Identify system dependencies, test environments, integrations, tools, and utilities needed to meet release and sprint goals.
Review automation test coverage and plan to increase or maintain coverage as enhancements are implemented.
Use AI tools to automate repetitive quality engineering work, including test documentation, test maintenance, defect categorization, regression impact analysis, and release readiness assessments.
Develop and refine prompts and workflows to improve the quality, accuracy, and consistency of AI-generated testing artifacts and automation assets.
Integrate AI-enabled capabilities into Quality Engineering processes to improve productivity, reduce manual effort, and increase software delivery velocity.
Use AI-powered coding assistants to design, develop, maintain, and optimize automated test scripts, frameworks, and supporting utilities.
Use AI-powered tools to help generate and maintain API tests, UI automation tests, service virtualization assets, and regression test suites.