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Microsoft Senior Software Engineer AI Data Platform CoreAI 
Taiwan, Taoyuan City 
929224248

16.10.2025

datasets that power model

is to build aAI modelwith secure, reusable, and compliant datasets.

sible for

Required Qualifications

  • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
    • OR equivalent experience.
  • 2+ years of experience in software engineering.
  • Proficiencyin one or more programming languages (e.g., C#, Java, Python).
  • Experience with distributed systems, cloud services (Azure, AWS, or GCP), or large-scale data pipelines.

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years

Preferred Qualifications

  • M.S. or Ph.D.in Computer Science, Engineering, or related field OR equivalent practical experience.
  • 4+ years of experience in software engineering.
  • Experience with data lifecycle management (e.g., ingestion, validation, discovery, governance).
  • Knowledge of privacy, compliance, and security practices in large-scale data platforms.
  • Familiarity with AI/ML workflows, training data preparation,andLLM-basedsynthetic data generationfor training,rewardmodelingand agents.
  • Strong problem-solving, communication, and collaboration skills

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities
  • Design and build scalable data pipelines and servicesto automate the dataset lifecycle (ingestion, registration, validation, PIIhandling, discovery, sharing, lineage), including intelligent agent-driven automation for key stages.
  • Develop secure and reliable infrastructurefor data access, entitlement management, and operational support across global time zones.
  • Implement governance and compliance toolingto ensure data integrity, auditability, and adherence to regulatory standards.
  • Create user-facing tools and APIsthat make datasets easily discoverable and reusable.
  • Contribute to strategic extensionssuch as continuous feedback loops, human-in-the-loop workflows, and data intelligence services for internal and external stakeholders.
  • (CoreAI, MAI, M365, GitHub, MSR, OCTO, and more