Quality Assurance Engineer

Nexiva•Denver, CO

2d•$60•Hybrid

About The Position

The Colorado Judicial Department is seeking an experienced Quality Assurance Engineer to support software quality through manual testing, test automation, performance testing, debugging, and quality-risk management. The ideal candidate will have strong hands-on experience developing and maintaining automated tests and will be comfortable working closely with developers, system personnel, business stakeholders, and management.

Requirements

3+ years of relevant QA and/or automated testing experience, OR 3+ years of experience as a Business Analyst or Software Engineer within the Colorado Judicial Department.
A bachelor's degree from an accredited college/university is preferred under the standard qualification path; relevant additional work experience may substitute for formal education on a year-for-year basis.
Strong understanding of software testing principles and QA best practices.
Hands-on experience with test automation and programming/scripting.
Strong debugging, analytical, and problem-solving skills.
Excellent written and verbal communication.
Ability to work effectively within cross-functional teams.
Meticulous attention to detail.
Candidates must be local to the Denver, Colorado area.
The position requires one day per week in person at the Ralph Carr Judicial Center.

Nice To Haves

Colorado Judicial Department experience is nice to have but is explicitly not required.
Zephyr Scale / Test Management
SQL / Relational Databases
NoSQL
DB2
MCP / AI-assisted testing
Agile

Responsibilities

Design, execute, maintain, and improve manual and automated test cases.
Perform functional, regression, API, performance, and exploratory testing.
Develop automated test scripts using technologies such as: Playwright TypeScript / JavaScript Java k6 MCP AI-assisted testing tools.
Translate business and functional requirements into detailed and comprehensive test cases.
Apply testing techniques such as boundary value analysis and equivalence partitioning.
Develop and maintain reusable automation frameworks using architectures such as: Data-driven Keyword-driven Hybrid BDD.
Integrate automated testing with Git/GitLab, version control, CI/CD pipelines, and test-management systems.
Use tools such as Zephyr Scale and GitLab to track test execution, defects, and progress.
Investigate failures using: Browser developer tools Application logs HTTP requests/responses Stack traces Heap dumps Other diagnostic information.
Identify the root cause of defects and provide developers with detailed, actionable information.
Design realistic performance-testing scenarios, including user journeys, test-data parameterization, and load models.
Identify performance bottlenecks, waste, variation, and other quality risks.
Assess quality risks based on their potential impact and likelihood and develop mitigation strategies.
Profile and analyze existing production data for testing purposes.
Work with relational and NoSQL databases and specialized test-data management/data-governance platforms.
Proactively identify quality issues early in the software development lifecycle.
Collaborate effectively with software engineers, system personnel, business teams, and management.
Participate in meetings and training as required.
Perform other duties as assigned.