Senior QA Analyst

Millennium Systems International • Parsippany, NJ

2d • Remote

About The Position

Millennium Systems International is seeking a forward-thinking Senior Quality Assurance Analyst to apply deep QA expertise and AI-enabled tools to improve how software is tested, validated, and shipped. The role focuses on using large language models, AI-powered test generation, intelligent automation, and data-driven insights to advance quality across the software delivery lifecycle.

The analyst will partner with engineering, product, and data teams to incorporate AI-assisted practices into QA workflows, including test case design, defect triage, predictive risk analysis, and self-healing test frameworks. This is a remote position, and candidates must reside in the United States.

The role also includes mentoring QA colleagues, evaluating and piloting new tools, improving repeatable quality practices, and championing responsible AI use across the organization. A bachelor's degree in a relevant technical field and demonstrated software QA or Quality Engineering experience are required.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field.
• Demonstrated professional experience in software Quality Assurance or Quality Engineering.
• Strong programming skills in one or more languages, such as Python, JavaScript, TypeScript, or C#, or an equivalent language.
• Experience building and maintaining test automation at scale using modern frameworks such as Playwright, Selenium, or Cypress, or similar tools.
• Hands-on experience using AI- or LLM-powered tools to improve QA efficiency, coverage, or speed.
• Experience with API testing and CI/CD integration.
• Strong analytical and problem-solving skills, with excellent attention to detail.
• Excellent written and verbal communication skills.
• Strong grounding in QA and Quality Engineering fundamentals, including end-to-end test strategy, risk-based testing, and release readiness.
• Experience designing and executing tests across web and API layers, including UI validation, regression, integration, and exploratory testing.
• Comfort working with SQL for test data setup, validation, and troubleshooting data integrity issues across environments.
• Understanding of CI/CD pipelines and integrating automated checks into build and deployment workflows.
• Experience working in Agile teams and contributing to sprint planning, test estimation, and release coordination.
• Ability or aptitude to use prompt engineering for context-aware QA workflows; evaluate and validate AI-generated suggestions rather than accepting them uncritically.
• Track record of mentoring junior QA engineers and improving team capabilities through knowledge sharing, pairing, and process improvement.
• Ability to identify quality gaps, recommend tooling, establish scalable best practices, communicate technical concepts to technical and non-technical stakeholders, and independently drive initiatives from concept through execution.
• Must reside in the United States.

Nice To Haves

• Experience with ETL or data warehouse testing using tools such as Fivetran, Databricks, or Snowflake.
• Familiarity with data modeling concepts such as star schemas and fact/dimension tables, and formats such as Parquet, CSV, and JSON.
• Experience validating end-to-end data flow from source systems through ETL processes to curated layers and visualization tools such as Quicksight, Tableau, or Power BI.
• Experience with data reconciliation, including row counts, aggregations, and KPI accuracy.
• Familiarity with non-functional testing, including performance, scalability, failover, reliability, and security.
• Hands-on experience with performance testing tools such as JMeter, Locust, or k6, or visual AI testing tools such as Applitools.
• Experience with backend/API testing tools such as Postman, REST Assured, or equivalent.
• Experience building custom AI agents, workflows, or integrations using LLM provider APIs.
• Familiarity with observability and monitoring tools such as Datadog, New Relic, or Grafana.
• Knowledge of security testing practices and basic OWASP principles.
• Experience with test management tools such as Azure DevOps, Jira, TestRail, or Zephyr.
• Familiarity with AI-assisted automation approaches such as self-healing locators, visual AI testing, or intelligent test selection and prioritization.

Responsibilities

• Define and execute AI-augmented test strategies across functional, integration, and automation testing layers.
• Use AI tools to accelerate test case design, automation script generation, defect root-cause analysis, and test documentation.
• Architect and maintain scalable test automation frameworks, including AI-assisted intelligent test selection, self-healing tests, and predictive defect analysis.
• Evaluate and pilot emerging AI-powered QA tools, create proof-of-concepts, and recommend adoption based on measurable quality and efficiency gains.
• Mentor and coach QA team members on foundational Quality Engineering practices and effective daily use of AI tools.
• Collaborate with engineering and product teams to embed quality earlier in development, advocate for shift-left testing, and support AI-assisted code review.
• Contribute to CI/CD pipeline quality gates and ensure automated functional checks are reliable, fast, and actionable.
• Establish and share best practices for responsible and effective AI use in Quality Engineering.

Benefits

• Paid time off: three weeks accruing from the first day, ten paid holidays throughout 2026, five paid sick days, and one personal day.
• Subsidized medical, dental, and vision plans.
• Company-paid life insurance and Accidental Death & Dismemberment insurance.
• Short-term and long-term disability insurance; the company fully covers long-term disability insurance.
• 401(k) plan with a 100% match on up to 4% of employee contributions.
• Unlimited access to Udemy online courses and learning and development opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior