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
We are seeking a capable Software Test Engineer with 3–5 years of hands‑on experience in software testing and working knowledge of Microsoft Configuration Manager (SCCM). In this role, you will contribute to the planning and execution of test strategies for SCCM deployments, validate configuration workflows, and help ensure the reliability of key system components such as triggers, stored procedures, and compliance policies.
You will work closely with engineering, architecture, and operations teams to support quality outcomes across enterprise environments. The role emphasizes hands‑on testing, automation contribution, and system analysis, with opportunities to grow technical depth and ownership over time.
Job Description
Key Responsibilities
- Participate in the design and execution of test strategies for SCCM deployments and configuration workflows.
- Perform validation of triggers, stored procedures, data integrity, and alignment with system and architectural specifications.
- Review and interpret code using at least one programming or scripting language; suggest improvements for quality, reliability, and testability.
- Execute system‑level configuration and testing tasks to validate SCCM operations and infrastructure behavior.
- Perform manual testing and contribute to automation initiatives to expand and improve test coverage.
- Maintain and enhance existing test cases and automation scripts; analyze test failures and implement fixes with guidance.
- Log detailed defect reports and collaborate with cross‑functional teams to support root‑cause analysis and issue resolution.
- Prepare test summaries, quality metrics, and risk inputs for project leads or senior engineers.
Job Requirements
- 3–5 years of experience in software testing, QA engineering, or related technical roles.
- Bachelor’s degree in Computer Science or a related field.
- Strong analytical and problem‑solving skills with the ability to understand complex systems.
- Ability to clearly communicate testing issues and produce clear, well‑structured test documentation in English.
- Proficiency in reading, understanding, and modifying code or scripts in at least one programming or scripting language.
- Working knowledge of SCCM architecture, deployment operations, and configuration management principles.
- Experience collaborating with engineers across development, architecture, and operations teams.
- Interest in growing toward technical leadership or mentoring responsibilities (not mandatory).
Top Skills
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.






