Quality Assurance Engineer

Millennium Systems International is an exciting and dynamic software company based in Parsippany, New Jersey. The company has built a reputation for producing high-quality, award-winning applications for the Wellness and Spa industries since 1987. Its commitment to delivering excellent customer service has contributed to its ongoing success. We are in search of a Quality Assurance Engineer – AI-Augmented Quality Engineering to help supplement the growth and scaling of the company. Millennium Systems International is honored to have been named one of New Jersey's Top Workplaces for 2021-2025! 

About the Role:
We are looking for a forward-thinking Quality Assurance Engineer who combines deep QA expertise with a passion for applying AI and intelligent tooling to transform how we test, validate, and ship software. This role goes beyond traditional testing — you will be a force multiplier for the QA organization, leveraging large language models, AI-powered test generation, intelligent automation, and data-driven insights to accelerate quality across the full software delivery lifecycle.

You'll partner closely with engineering, product, and data teams to embed AI-assisted practices into everyday QA workflows — from smarter test case design and automated defect triage to predictive risk analysis and self-healing test frameworks. This is a remote position.

What We're Looking For:

Core Quality Engineering Skills

• Strong foundation in Quality Assurance and Quality Engineering fundamentals, including end-to-end testing strategy, risk-based testing, and release readiness.
• Proven experience designing and executing tests across web and API layers — including UI validation, regression, integration, and exploratory testing.
• Hands-on proficiency with test automation frameworks such as Playwright, Selenium, or Cypress, with the ability to architect scalable, maintainable test suites.
• Comfortable working with SQL for test data setup, validation, and troubleshooting data integrity issues across environments.
• Solid understanding of CI/CD pipelines and the ability to integrate automated checks into build and deployment workflows.
• Experience working within Agile teams, contributing to sprint planning, test estimation, and release coordination.

AI & Intelligent Tooling Skills

• Demonstrated ability to leverage AI-powered tools (e.g., GitHub Copilot, Claude, ChatGPT, Cursor, or similar LLM-based assistants) to accelerate test case generation, script authoring, defect analysis, and documentation.
• Experience with — or strong aptitude for — prompt engineering techniques to extract high-quality, context-aware outputs from AI models for QA workflows.
• Familiarity with AI-assisted test automation approaches such as self-healing locators, visual AI testing (e.g., Applitools), or intelligent test selection/prioritization.
• Ability to evaluate, pilot, and integrate new AI-powered QA tools into existing processes, measuring impact on speed, coverage, and defect detection.
• Understanding of how to use AI for test data generation, synthetic data creation, and edge-case discovery.
• Awareness of the limitations and risks of AI-generated outputs — able to validate, review, and refine AI suggestions rather than accepting them uncritically.

Leadership & Growth Mindset

• A track record of mentoring junior QA engineers and elevating team capabilities through knowledge sharing, pairing, and process improvement.
• Ability to champion and evangelize AI-augmented QA practices across the engineering organization.
• Experience identifying quality gaps, recommending tooling, and establishing repeatable best practices that scale.
• Strong communication and documentation skills — able to articulate technical concepts clearly for both engineering and non-technical stakeholders.
• Proactive, self-directed, and dependable, with a history of independently driving initiatives from concept through execution.

Responsibilities:

• Define and execute AI-augmented test strategies across functional, integration, and automation testing layers.
• Leverage AI tools to accelerate QA workflows — including test case design, automation script generation, defect root-cause analysis, and test documentation.
• Architect and maintain scalable test automation frameworks, integrating AI-assisted capabilities such as intelligent test selection, self-healing tests, and predictive defect analysis.
• Evaluate and pilot emerging AI-powered QA tools, building proof-of-concepts and making recommendations for adoption based on measurable quality and efficiency gains.
• Mentor and coach QA team membe