Microsoft Advertising is seeking a Principal Software Engineering Manager to lead engineering teams within the Ads Trust & Safety AI Platform. The role involves leading development of platform capabilities including advertiser and domain intelligence, AI-assisted investigation, model serving, decisioning, enforcement, human review, observability, and risk/fraud protection. The candidate will set technical direction, manage and grow engineering teams, and deliver reliable, scalable, and secure production systems. Required qualifications include a Bachelor's degree in Computer Science or related field, 8+ years of engineering management experience, technical expertise in AI/ML systems and related platforms, and strong communication skills. Preferred experience includes Trust & Safety, fraud detection, adversarial systems, and human-in-the-loop workflows. The position is based in Bengaluru, India.
What you'll do
Lead and grow a highly technical engineering team responsible for core areas of the Ads Trust & Safety AI Platform including advertiser/domain intelligence, content moderation, AI-assisted investigation, decisioning, enforcement, human review, observability, and risk/fraud protection
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Evangelize the team’s platform capabilities across Microsoft Ads and relevant Microsoft Trust teams, helping partner teams adopt shared systems
Requirements
Bachelor’s Degree in Computer Science or related technical field
8+ years of EM experience leading software engineering teams, including experience managing senior engineers, technical leads & managers
Experience leading engineering teams that build and operate large-scale production systems with meaningful reliability, scalability, latency, correctness, availability, security, and operational requirements
Technical depth in 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 to translate ambiguous requirements into shipped engineering systems
Exposure to production AI/ML systems including LLM-based workflows, retrieval-augmented generation, model orchestration, automated reasoning, human-in-the-loop systems, AI-assisted operational tooling, or agentic workflows
Understanding of production requirements for AI or decision systems including evaluation, observability, quality measurement, rollout safety, fallback behavior, latency/cost tradeoffs, explainability, governance, and operational reliability
Experience building high-integrity systems where decisions must be auditable, reproducible, explainable, governed, and secure
Demonstrated ability to hire, grow, coach, and retain strong engineering talent in complex technical areas
Strong communication skills including ability to explain technical tradeoffs, risks, execution plans, and platform strategy to engineering, science, product, policy, and business stakeholders
Preferred: Experience in Trust & Safety, Fraud, Abuse, Risk, Security, Ads Quality, Marketplace Integrity, Policy Enforcement, or advertiser protection systems
Preferred: Experience with adversarial systems such as phishing, malware, cloaking, account takeover, payment abuse, fake identities, compromised advertisers, coordinated fraud, and policy evasion
Preferred: Experience building or managing teams that build 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
Preferred: Experience managing teams that build model-serving, decisioning, enforcement, workflow, or human-review platforms
Preferred: Experience with entity intelligence, knowledge graphs, web crawling, domain reputation, business identity resolution, provenance, evidence extraction, or risk scoring
Preferred: Experience designing or operating human-in-the-loop review systems, appeals workflows, audit platforms, policy reasoning systems, or enforcement governance mechanisms
