Microsoft Principal Security AI Software Engineer 

Taiwan, Taoyuan City 

472153688

• Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field
• 10+ years of industry experience in applied AI/ML, data science, or software engineering roles
• Strong hands-on programming skills
• Proven experience designing or evaluating AI/ML systems and/or benchmarking pipelines
• At least 2 years of experience in the security domain (e.g., threat detection, anomaly detection, SOC environments)
• Familiarity with ML Ops practices – taking models from experimentation to production
• Demonstrated ability to collaborate across research, product, and engineering teams
• Experience with Generative AI, agentic systems, or LLM-based tools
• Strong understanding of data quality, validation, and governance practices
• Background in both AI and Security contexts, particularly where the two intersect
• Growth mindset, strong sense of ownership, and ability to mentor junior team members

Preferred:

• Experience working with or building evaluation datasets, test harnesses, or performance metrics for AI systems
• Familiarity with modern Generative AI benchmarks
• Familiarity with AI security vulnerabilities
• Academic publishing or prior contribution to research communities

Other RequirementsAbility 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 background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Understanding of secure execution environments for safe workload handling, including potential exposure to malware analysis.

• Design and optimize Generative AI benchmarks and evaluations to support efficient model training, agentic system evaluation, and solution deployment within Microsoft Security AI.
• Collaborate with product, research and engineering to ensure seamless integration of evaluation datasets and test harnesses into AI-driven security solutions.
• Curate scalable, reliable, and secure datasets that enable benchmarking and evaluation of core security tasks such as threat intelligence, anomaly detection, and penetration testing.
• Ensure data integrity and reliability by implementing rigorous validation, monitoring, and governance practices.
• Drive innovation in data engineering by exploring new technologies, architectures, and methodologies to improve AI security performance.