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
- Execute and monitor Build Verification Tests (BVT) for each build; perform quick validation, identify blockers, and communicate results concisely & timely.
- Maintain and extend automated regression suites (create new automated test cases, update existing scripts, and improve coverage based on product changes).
- Debug automation failures by analyzing logs, screenshots, traces, and test telemetry to determine root cause (test script issue, product defect, or environment/config problem).
- Triage and reduce flaky tests by improving test reliability, adding better waits/assertions, and strengthening test data/environment setup.
- File high-quality bugs with clear repro steps, expected vs. actual results, and supporting evidence; follow up with developers through fix verification.
- Collaborate with SDE/SDET/DevOps teams to keep test environments healthy and to integrate automated tests into CI pipelines.
- Leverage AI tools responsibly to accelerate test design, failure analysis, and documentation (e.g., summarizing logs, generating test ideas, improving readability of test code).
- Execute system-level configuration tasks to validate end-to-end SCCM operations and infrastructure behavior.
- Perform manual testing, drive automation initiatives, and optimize test coverage across automation frameworks.
- Refactor and enhance legacy test cases and automation scripts; conduct analysis of automated test failures and provide resolutions.
- Produce detailed, actionable defect reports and collaborate with cross-functional teams for root-cause analysis and issue resolution.
- Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent practical experience).
- Good knowledge in software testing, QA, or test automation (internship/academic projects are welcome).
- Demonstrated AI experience or strong interest (e.g., using AI tools for coding/testing, coursework, projects, experimentation with LLMs) and willingness to apply AI to improve day-to-day engineering productivity.
- Hands-on experience (or strong fundamentals) in at least one programming/scripting language such as Python, C#, JavaScript/TypeScript, or PowerShell.
- Solid debugging/troubleshooting skills: ability to read logs, interpret failures, isolate variables, and propose next-step experiments.
- Understanding of test fundamentals: test case design, regression testing, defect lifecycle, and quality mindset.
- Familiarity with test automation frameworks/tools is a plus (e.g., Playwright, Selenium, Cypress, Appium, NUnit/PyTest, REST API testing).
- Exposure to CI/CD and version control (Git) is a plus; experience running tests in pipelines is beneficial.
- Strong written and verbal communication in English; able to write clear bug reports and concise test summaries.
- Bachelor’s degree in computer science or a related field, with a strong sense of ownership and professional integrity.
- Strong analytical and problem-solving abilities with the capability to understand
- Proficiency in reading, understanding, and modifying code in at least one programming language or scripting language.
- Knowledge of SCCM architecture, deployment operations, and configuration management principles (is a plus).
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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.
