**Role & seniority: ** Quality Engineering (QE) / QA, likely mid-to-senior (mentoring/leading responsibilities)

**Stack/tools: **

Automation: Playwright (preferred), Selenium (or equivalent)
Programming: Python (preferred), or C#, Java
Performance/load testing: JMeter (or equivalent)
Data/analytics: Databricks, Microsoft Fabric (preferred); ETL/data pipeline testing
AI/ML testing: LLM behavior, prompt robustness, model output/performance metrics
Cloud: Azure preferred
Other: Agile/QE documentation; relevant certs (Azure/Microsoft/Agile) plus
Top 3 responsibilities:
- Define/advise on test planning and strategies across functional, system, data, and AI/LLM components
- Execute manual + automated testing to ensure full coverage; maintain test cases/results and feedback loop
- Design/validate test data, data pipelines/infrastructure, and support defect triage
Must-have skills:
- Strong QA/QE methodologies and test planning
- Automation proficiency (Playwright/Selenium) + solid programming
- Hands-on performance/load testing experience (e.g., JMeter)
- Ability to test data pipelines/ETL and AI model/LLM behavior
Nice-to-haves:
- Databricks/Fabric experience
- Azure experience; QE/Agile/Azure certifications
- Mentoring experience; process/quality documentation leadership
Location & work type:
- Work shift: 5PM–2AM
- Location not

Full Description

Apply knowledge of Quality Engineering and testing areas (Automation, Performance, Data quality, AI, While box, Blackbox) to define and advise in test planning
Drive high-quality delivery by performing both manual and automated testing, ensuring full coverage across functional, system, data, and AI components.
Assist or Lead the design and implementation of comprehensive test strategies, quality processes, and documentation for assigned project.
Maintain accurate record results, test cases, and share feedback to the project team
Ensure all QE deliverables meet quality standards, aligning with project objectives and organizational best practices.
Actively assist or lead defect triage process
Develop and validate test data, data pipelines, and infrastructure from both functional and system perspectives.
Evaluate and test machine learning models, including LLM behavior, prompt robustness, model outputs, and performance metrics.
Mentor junior team members, promote QE best practices, and contribute to continuous improvement initiatives across the Quality engineering practice.

Bachelor’s degree in computer science, or a closely related discipline.
Solid experience in QA methodologies, test planning, automation, and quality engineering practices.
Strong proficiency in automation tools such as Playwright (highly preferred), Selenium, or equivalent frameworks.
Solid programming skills in Python (highly preferred), C#, Java, or similar languages.
Hands-on experience testing data pipelines, ETL workflows, and analytics platforms (Databricks, Fabric preferred).
Understanding of machine learning principles, model evaluation metrics and AI system behavior
Extensive experience on Load and Performance Testing (has used JMeter and other equivalent tools)
Ability to test LLM behavior, prompts, and AI model outputs.
Ability to execute comprehensive test plans for AI models and systems.
Excellent analytical, problem-solving, communication, and presentation skills.
Demonstrated ability to work cross-functionally and influence engineering teams.
Passion for innovation, continuous learning, and staying current with emerging QE and AI technologies.
Relevant certifications (Azure, Microsoft, Agile, etc.) are a plus.
Experience with cloud platforms, especially Azure, is preferred

Work shift: 5PM - 2AM