Senior Principal Architect : Ads Trust & Safety AI Platform

Microsoft Advertising is seeking a Senior Principal Architect to define and drive the next generation of the Ads Trust & Safety AI Platform. This role involves setting technical direction, shaping platform strategy, and building durable systems that protect users, advertisers, and partners from harm.

Overview

The Ads Trust & Safety AI Platform is crucial for protecting users from harmful content, advertisers and publishers from fraud and abuse, and ensuring Microsoft Ads operates with strong policy, privacy, security, compliance, and regulatory integrity.

Responsibilities

AI Platform Architecture and Technical Strategy

• Define the long-term architecture for the Ads Trust & Safety AI Platform across ingestion, signal acquisition, entity intelligence, retrieval, model orchestration, agentic workflows, decisioning, enforcement, human review, audit, and measurement.
• Translate broad Trust & Safety, Risk, Fraud, Security, and Policy needs into reusable platform capabilities.
• Establish reference architectures, design principles, technical standards, and engineering patterns for high-integrity AI and decisioning systems.
• Drive architecture choices across latency, throughput, quality, cost, explainability, governance, reliability, and operational safety.
• Identify critical platform gaps and create a roadmap that balances near-term delivery with long-term leverage.

Deep Research Agents and AI-Assisted Investigation

• Architect platform for Deep Research Agents that investigate domains, landing pages, advertisers, business entities, ownership patterns, web presence, reputation, policy risk, and fraud signals.
• Architect workflows that combine retrieval, crawling, structured evidence extraction, LLM reasoning, policy grounding, risk scoring, and human-in-the-loop review.
• Architect guardrails for agentic systems, including source provenance, confidence scoring, hallucination controls, audit logs, escalation paths, and human override.
• Partner with Applied Science to convert AI research prototypes into production systems with clear quality, latency, cost, reliability, safety, and governance targets.

Entity Intelligence, Decisioning, and Enforcement

• Architect systems for high-fidelity understanding of domains, websites, landing pages, advertisers, business identities, ownership structures, relationship graphs, reputation, and provenance.
• Design real-time, nearline, and batch scoring systems for policy enforcement, fraud detection, abuse prevention, advertiser risk scoring, and marketplace protection.
• Evolve abstractions for model orchestration, feature lookup, signal stores, retrieval, model versioning, decision logging, policy controls, fallbacks, and experimentation.

Security, Risk, and Fraud Platform

• Architect systems to detect, learn, and mitigate adversarial behavior across the advertiser lifecycle.
• Build sequential and event-based risk systems that reason over advertiser behavior over time.

Cross-Microsoft Collaboration, Industry Learning, and Technical Leadership

• Collaborate across Microsoft, Safety, Security, Responsible AI, Identity, and partner teams to create shared platform capabilities for risk detection, abuse prevention, evidence generation, and enforcement governance.
• Evangelize a coherent Trust & Safety AI platform strategy across Microsoft.
• Learn from industry peers and translate those learnings into practical platform improvements.

Qualifications

• Bachelor’s Degree in Computer Science or related technical field AND 15+ years of professional software engineering experience.
• 8+ years of senior technical leadership experience influencing engineers, technical leads, architects, applied scientists, or cross-functional engineering teams.
• Proven experience architecting and delivering large-scale production systems.
• Deep technical experience in AI/ML systems, agentic systems, model-serving infrastructure, decisioning systems, distributed systems, data platforms, workflow platforms, risk platforms, security platforms, or Trust & Safety systems.
• Experience building or technically leading production AI/ML systems.

Preferred Qualification

• Deep domain experience in Trust & Safety, Fraud, Abuse, Risk, Security, Ads Quality, Marketplace Integrity, Policy Enforcement, or advertiser protection systems.
• Experience with adversarial systems, including phishing, malware, cloaking, account takeover, payment abuse, fake identities, compromised advertisers, coordinated fraud, and policy evasion.
• Experience building Deep Research Agents, investigation agents, reviewer-assist systems, retrieval-augmented generation systems, LLM-powered operational workflows, or AI systems that produce grounded evidence for human or automated decisions.