Source description
About the role
Quality Engineering & Test Execution
Execute test plans and test cases as directed by senior QE team members.
Perform basic functional, regression, and integration testing across Web, API, and/or Data components as applicable.
Identify, document, and track defects accurately in our bug tracking system (e.g., Jira), including clear reproduction steps and impact.
Contribute to the creation and maintenance of test data needed for test execution.
Assist in troubleshooting and investigating issues by reproducing defects, gathering logs, and validating fixes.
Contribute to basic test scripts (manual and automated) under guidance, following established patterns and standards.
Collaboration, Communication & Ownership
Participate in team meetings, providing clear status updates on assigned tasks.
Communicate testing progress, risks, and issues to your team in a clear and concise way, including to non-technical stakeholders when needed.
Ask questions and seek clarification proactively to fully understand requirements, scope, and expected behavior.
Follow through on commitments, take responsibility for your work, and deliver assigned tasks on time with close supervision.
Collaborate with your team to unblock issues within the scope of your work, escalating when needed.
Quality Practices, Processes & AI Tools
Learn and adhere to established QE standards, processes, and best practices (including test case structure, defect reporting, and regression workflows).
Build a basic understanding of the software development lifecycle (SDLC) and how quality is embedded throughout.
Begin working within Agile/Scrum practices (e.g., participating in sprint ceremonies, using user stories, understanding acceptance criteria).
Assisted Scripting: Use AI-powered code completion tools (e.g., GitHub Copilot) to help write simple test automation scripts or snippets under supervision.
AI-Suggested Test Cases: Leverage AI tools to generate basic test case ideas and scenarios from requirements or user stories, then refine them with guidance.
Intelligent Search: Use AI-enhanced search within bug tracking and documentation systems to quickly find duplicate issues, related tickets, or supporting documentation.
Build awareness of how to find information and who to ask across the company (e.g., “Who can answer X?” or “Where is Y documented?”).
More at TrueML