Principal Software Engineering Manager, AI Experiences - Monetization

Microsoft•Redmond, WA

1d•$142,800 - $304,200•Hybrid

About The Position

As part of Microsoft AI Experiences, the Monetize Platform powers an open, transparent advertising marketplace connecting advertisers and publishers across thousands of websites and applications. Its buy-side and sell-side technology enables customers to access and trade premium advertising inventory efficiently at global scale. The Monetize Real-time Platform executes dynamic advertising auctions in less than 100 milliseconds, handles more than 8 million queries per second and approximately 100 billion requests per day, and generates more than 150 TB of new data daily. Its distributed systems support auction execution, ad delivery, and marketplace accounting under demanding performance and reliability constraints. Microsoft is seeking a Principal Software Engineering Manager to lead the Infrastructure, Operations and Shared Tech team. The team owns foundational infrastructure, production operations, and selected shared software services and libraries powering the real-time platform. These capabilities include distributed caching, model and configuration distribution, low-latency decision-service integration, traffic management, and high-volume logging and streaming pipelines. The manager will combine people leadership with technical judgment to advance platform architecture, operational excellence, and engineering productivity across hybrid on-premises and Azure environments. The role guides engineers working on performance-sensitive C/C++ services, shared-runtime modernization, distributed-cache migrations, and integration of model-backed capabilities into real-time serving. The manager owns the team's roadmap and delivery, develops engineers, and partners across platform, product, machine learning, and infrastructure teams to deliver reliable shared capabilities. AI Experiences employees living within a 50-mile commute of a designated Microsoft Hub in the U.S. are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Requirements

Bachelor's Degree in Computer Science or a related technical field and 6+ years of technical engineering experience coding in languages including C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
3+ years of people management experience leading software engineering teams, including coaching, performance management, and career development.
Experience designing, delivering, and operating large-scale distributed systems, including performance-sensitive backend services.
Experience leading cross-team engineering initiatives involving shared platforms, infrastructure, or production-service modernization.
Solid understanding of software architecture and production reliability, including concurrency, resource management, and distributed-system failure modes.
Experience with high-performance C/C++ software on Linux, including multithreading, asynchronous I/O, memory ownership, profiling, and efficient data structures.
Experience building shared libraries or foundational services adopted by multiple engineering teams, including interface evolution and backward compatibility.
Experience with distributed caches or key-value systems such as Aerospike, Garnet, Redis, or comparable technologies, including replication, failover, capacity planning, and client integration.
Experience with Kafka or comparable streaming systems and high-throughput logging or data-distribution pipelines.
Experience integrating machine-learning scores or model-backed decisions into latency-sensitive production services; model-training experience is not required.
Experience with traffic shaping, rate limiting, admission control, or other mechanisms for balancing throughput, capacity, and business value.
Experience operating Azure and hybrid infrastructure, including virtual machine scale sets, networking, storage, and infrastructure-as-code technologies such as Terraform or Bicep.
Experience with configuration-management tools such as Puppet or comparable systems, CI/CD pipelines, and automated build and test environments.
Experience delivering migrations using feature flags, experimentation, shadow traffic, staged rollouts, and rollback strategies.
Experience with observability technologies such as Grafana or OpenTelemetry and with service-level objectives, incident management, and operational automation.

Nice To Haves

Master's Degree in Computer Science or a related technical field and 8+ years of technical engineering experience coding in languages including C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
Bachelor's Degree in Computer Science or a related technical field and 12+ years of technical engineering experience coding in languages including C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
Experience with advertising auctions, pricing, inventory-quality controls, or other high-volume real-time transaction systems.

Responsibilities

Lead, hire, coach, and develop a team spanning infrastructure, operations, and shared-platform software; establish expectations, support career development, and foster an inclusive culture of technical excellence and accountability.
Own the team's roadmap and delivery by translating platform and product needs into priorities, architectural plans, and measurable outcomes, balancing feature delivery with reliability, security, technical debt, infrastructure cost, and operational sustainability.
Guide the design and evolution of reusable services, libraries, interfaces, and runtime components used across real-time applications; establish clear ownership boundaries and maintain compatibility as systems evolve.
Improve low-latency software engineering, including concurrency, asynchronous execution, memory safety, data structures, and resource efficiency for high-throughput Linux services; uphold standards for design reviews, code quality, and automated testing.
Lead distributed-cache and state-service integration, migration, capacity planning, replication, failover, and observability, ensuring predictable behavior under timeouts, partial failures, and changing workloads.
Partner with machine learning and auction teams to integrate model scores and decisions into real-time services, including traffic shaping and dynamic pricing, while preserving latency budgets, decision correctness, fallback behavior, and experimentation controls.
Improve high-volume logging and streaming infrastructure, including data collection, buffering, batching, transport, and downstream integration; address throughput, backpressure, data integrity, and recovery across distributed pipelines.
Deliver infrastructure-as-code and shared-service migrations to Azure through staged validation, controlled cutovers, and practical rollback plans; coordinate dependencies across networking, storage, and data-platform teams.
Improve service-level objectives, monitoring, alerting, diagnostics, and on-call practices; guide incident response and blameless postmortems, turning recurring production issues into durable engineering improvements.
Advance build systems, CI/CD, deployment automation, configuration management, and reusable tooling; embed security and privacy requirements into application and infrastructure design.