Principal Software Engineering Manager | Ads Trust & Safety AI Platform

Microsoft Advertising is seeking a Principal Software Engineering Manager to lead a key engineering area within the Ads Trust & Safety AI Platform. This team builds platform capabilities for advertiser and domain intelligence, AI-assisted investigation, model serving, decisioning, enforcement, human review, observability, and risk/fraud protection.

The ideal candidate has technical credibility to guide architecture, management experience to build and grow a high-performing team, and operational discipline to deliver reliable platform capabilities in a complex, high-integrity environment.

Responsibilities:

• Lead and grow a highly technical engineering team responsible for core areas of the Ads Trust & Safety AI Platform.
• Set technical direction and execution priorities across platform delivery, quality, reliability, operational excellence, and live-site readiness.
• Hire, coach, and develop engineers and technical leads.
• Own delivery for major platform components.
• Partner with senior ICs, architects, and other teams to translate business needs into scalable platform capabilities.
• Drive productionization of AI/ML and agentic capabilities.
• Deliver real-time, nearline, and batch decisioning systems for policy enforcement, content moderation, fraud detection, and marketplace protection.
• Evangelize the team’s platform capabilities across Microsoft Ads and relevant Microsoft Trust teams.

Qualifications:

• Bachelor’s Degree in Computer Science or related technical field.
• 8+ years of EM experience leading software engineering teams.
• Experience leading engineering teams that build and operate large-scale production systems.
• Technical depth in one or more of the following areas: AI/ML systems, model-serving infrastructure, decisioning systems, distributed systems, data platforms, workflow platforms, risk platforms, security platforms, or Trust & Safety systems.
• Experience partnering with Applied Science, Product, or cross-functional stakeholders.
• Exposure to production AI/ML systems.
• Understanding of production requirements for AI or decision systems.
• Experience building high-integrity systems.
• Demonstrated ability to hire, grow, coach, and retain strong engineering talent.
• Strong communication skills.