Microsoft

Principal Software Engineering Manager - Ads

Bangalore · On-site · 15+ yrs · Principal · Full-time

  • distributed systems
  • machine learning
  • ai infrastructure
  • decision systems
  • data platforms

Lead engineering for Microsoft Ads Quality systems at scale with 15+ years experience and AI/ML infrastructure expertise.

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Posted 14 Oct 2026 · found on Microsoft's own careers page

Interview prep: questions this posting points to

Written from 8 current Platform postings on Microsoft's own careers page — not questions Microsoft has asked.

  1. Fabric is described as a 'high throughput and multi-tenant service.' Walk me through how you'd design tenant isolation so one noisy customer can't degrade performance for others, and how you'd detect that it's happening in production.
    From the posting: “Work with all aspects of a high throughput and multi-tenant service.``` · Collaborate effectively within the team and with partner teams across Microsoft. · Be part of the on-call rotation for maintaining service health. The fragment used: "high throughput and multi-tenant service"”
  2. You're on-call for Fabric and get paged for a sudden spike in latency affecting a subset of tenants during peak hours. Walk me through how you'd triage this.
    From the posting: “Be part of the on-call rotation for maintaining service health.”
  3. We've got a metric that says our service reliability is degrading, but you're also supposed to be shipping a new feature your product manager is excited about. How would you handle that tension?
    From the posting: “Champion operational excellence via established metrics, process governance, and policy controls for regular assessment and improvement.”
See all 63 questions More on this prep
Read the full job description

Overview

Microsoft Advertising makes billions of decisions every day across search, native, shopping, display, audience, and AI-powered advertising experiences. We are looking for a Principal Software Engineering Manager to lead the engineering organization building Ads Quality systems at global scale. The team builds the software systems that turn quality signals and models into dependable production decisions across ads, landing pages, advertisers, businesses, accounts, and changing behavioral patterns. This is a deeply technical engineering leadership role.

You will lead senior engineers and engineering managers while remaining close to architecture, distributed systems, production AI, measurement, and operational quality.

Responsibilities

Own the engineering strategy and execution for Ads Quality systems across signal processing, entity systems, model execution, decisioning, feedback, and measurement. Build scalable real-time, nearline, and offline systems supporting very large volumes and demanding reliability requirements. Create the production infrastructure that allows new models and signals to move rapidly from experimentation into safe global deployment. Partner with Applied Science on model integration, evaluation, experimentation, serving trade-offs, and productionization.

Build common engineering foundations for heterogeneous AI workloads including classifiers, multimodal models, LLMs, agents, and deterministic systems. Develop feedback, observability, experimentation, and diagnostic systems that make quality problems easy to find and fast to fix. Drive architectural simplification and prevent the quality stack from becoming a collection of bespoke pipelines and one-off services. Lead and grow senior engineers, engineering managers, and technical leaders capable of independently owning complex areas.

Drive difficult programs across organizational boundaries and maintain a high bar for architecture, engineering quality, and production ownership.

Qualifications

15+ years of software engineering experience, or equivalent technical depth. Significant experience leading senior engineers, engineering managers, or large engineering organizations. Strong technical depth in distributed systems, AI/ML infrastructure, decision systems, or large-scale data platforms. Experience building production systems that operationalize machine-learning models at significant scale.

Strong judgment around latency, throughput, reliability, freshness, cost, observability, and operational safety. Ability to challenge architecture, understand failure modes This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.

If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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