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Skills
Artificial Intelligence (AI)unmatched
Atlassian JIRAunmatched
Automationunmatched
Bug Tracking/Defect Managementunmatched
Continuous Deployment/Deliveryunmatched
Continuous Integrationunmatched
Detail Orientedunmatched
DevOpsunmatched
Dockerunmatched
Gitunmatched
GitHubunmatched
Home Automationunmatched
JavaScriptunmatched
Jenkinsunmatched
Manufacturing/Production Testingunmatched
Python Programming/Scripting Languageunmatched
Quality Assuranceunmatched
Scalable System Developmentunmatched
Scripting (Scripting Languages)unmatched
Software Development Lifecycle (SDLC)unmatched
Software Testingunmatched
Technical Supportunmatched
Test Automationunmatched
Test Caseunmatched
Test Harnessunmatched
Test Plan/Scheduleunmatched
Test Suiteunmatched
Test Toolsunmatched
Testingunmatched
Usability Engineeringunmatched
Use Casesunmatched
User Documentationunmatched
User Interface/Experience (UI/UX)unmatched
Description
Overview
We are seeking a highly skilled and experienced Senior/Staff QA Engineer to support a critical customer engagement. This role is ideal for a detail-oriented tester who thrives owning quality end-to-end — someone equally comfortable writing precise manual test cases and building automated coverage for a fast-moving agentic AI product.
The successful candidate will work closely with the Delivery Lead/Solutions Architect and customer engineering stakeholders to ensure product quality from initial test planning through final release.
Required Credentials
5+ years of professional QA experience, with at least 2+ years at a senior or staff level.
Demonstrated experience testing production software through a full Application Development Lifecycle (ADLC).
Required Qualifications
ADLC Expertise: Strong understanding of the Application Development Lifecycle — from requirements through release and support.
UI/UX Acumen: Solid UI/UX understanding, with the ability to evaluate usability and flag design/interaction issues, not just functional bugs.
AI Agent Testing: Hands-on experience testing AI Agent use cases — including conversational flows, agent decision-making, tool/function calling, and edge-case or failure-mode behavior.
Automation Frameworks: Proven experience with automated testing frameworks and building maintainable, scalable test suites.
Infrastructure Management: Ability to stand up and manage a Playwright cluster to run automated end-to-end (E2E) testing against a live agent platform.
Autonomy: Ability to independently define clear, well-structured test cases from ambiguous or evolving product requirements.
Lifecycle Ownership: Experience driving full E2E QA lifecycle ownership: test planning, execution, defect triage, regression, and sign-off.
Automation Frameworks: Deep expertise with Playwright (including cluster management and parallel execution).
Languages: Proficiency in JavaScript / TypeScript or Python for writing automation scripts.
AI/LLM Tools: Familiarity with testing LLM outputs, prompt evaluation frameworks, or conversational AI testing tools.
CI/CD & DevOps: Experience integrating automated test suites into pipelines (e.g., GitHub Actions, GitLab CI, Jenkins) and working with Docker containerization.
Defect Tracking & Tools: Proficiency with Git, Jira, and modern test management tools.
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