About Centific
Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem—comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets—to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.
Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.
About Job
Key Responsibilities
Develop, maintain, and execute automated test cases for Intune features across Web UI, Mobile (Android/iOS), and Windows devices
Perform functional, regression, compatibility, UX, and end-to-end testing across multiple platforms and OS versions
Configure and validate devices enrolled under various Intune compliance and policy scenarios
Troubleshoot failures by deep diving into logs, UI traces, and system configurations
Actively contribute to build verification tests and sprint sign-off validations
Implement best practices in test data generation, environment setup, and automation stability
Collaborate with developers and SMEs to identify root causes and drive defect fixes
Continuously optimize automation frameworks and pipelines to improve coverage and stability
Work with CI/CD tools (Azure DevOps) to enable unattended and scalable test execution
Provide crisp reporting and insights using dashboards (Power BI / ADO Reports)
Own QA activities for one or more applications/modules.
Define and execute the overall testing strategy.
Identify quality risks early in the development lifecycle.
Drive automation and continuous improvement.
Mentor junior and senior test engineers.
Review automation architecture and implementation.
Communicate quality status, risks, dependencies, and release readiness to stakeholders.
Represent the QA team in customer-facing discussions.
Establish quality metrics and dashboards.
Improve test processes to reduce manual errors and production defects.
Review test estimates, coverage, execution results, and defect report
Drive resolution of critical quality issues and release risks.
Technical Skills Required
Must-have:
6+ years of experience in SDET / Automation
Strong scripting/coding skills in TypeScript, JavaScript, C#, or Python (TypeScript and C# are mandatory)
Hands-on automation experience using Playwright / Selenium / Appium (Playwright is mandatory and primary preference, Selenium /Appium as last preference)
Working knowledge of Android, iOS, and Windows 10/11 environments
Experience validating Enterprise Mobility Management (EMM) or similar device workflows
Understanding of AAD, policy deployment, enrollment flows, identity & security models
CI/CD and version control experience (Azure DevOps, Git) (working knowledge)
Good to have:
Experience in Graph API, backend validation, and service-level testing
Knowledge of PowerShell, ADB tools, Xcode tools, Wireshark
Familiarity with CMSherlock / Geneva Synthetics or similar automation tools
Exposure to Intune, Endpoint security, MDM/EMM platforms, UEM solutions
Basic understanding of LLM/Copilot assisted automation or self-healing frameworks
Skills Required
- 6+ years of experience in SDET or test automation
- Strong coding skills in TypeScript and C#
- Strong scripting or coding skills in JavaScript or Python
- Hands-on automation experience with Playwright
- Experience with Selenium or Appium automation
- Working knowledge of Android, iOS, and Windows 10/11 environments
- Experience validating Enterprise Mobility Management or similar device workflows
- Understanding of Azure Active Directory, policy deployment, enrollment flows, identity, and security models
- Working knowledge of Azure DevOps and Git
- Experience with Graph API, backend validation, and service-level testing
- Knowledge of PowerShell, ADB, Xcode tools, and Wireshark
- Familiarity with CMSherlock, Geneva Synthetics, or similar automation tools
- Exposure to Intune, endpoint security, MDM/EMM, or UEM platforms
- Basic understanding of LLM or Copilot-assisted automation and self-healing frameworks
Centific Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Centific and has not been reviewed or approved by Centific.
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Healthcare Strength — Feedback suggests core medical, dental, and vision coverage is comprehensive, with mental‑health support included. U.S. offerings also include HSA/FSA and are described as solid insurance options.
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Flexible Benefits — Feedback suggests flexible hours and work‑from‑anywhere options are widely promoted, with flexible PTO available in some contexts. Learning stipends and development programs add adaptable elements to the package.
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Parental & Family Support — Feedback suggests paid parental leave is explicitly available to all parents. This positions family leave as an accessible component of the overall package.
Centific Insights
What We Do
Zero distance innovation for GenAI creators and industries Expertly engineering platforms and curating multimodal, multilingual data, we empower the ‘Magnificent Seven’ and enterprise clients with safe, scalable AI deployment We a team of over 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We bring platforms, partners and 1.8 million vertical domain experts to create high-quality pre-trained datasets, fine-tuned industry-specific LLMs, and RAG pipelines supported by vector databases. These innovations can reduce GenAI costs by up to 80% and bring GenAI solutions to market 50% faster in 230 locales.
