Mountain View, United States; Redmond, United States
Full job description
Microsoft Advertising Mediation Service (MMS) is a real-time auction and mediation platform built on Go, processing OpenRTB traffic globally across Azure regions. The Principal Software Engineer will lead technical direction for MMS architecture, including request hot path, auction engines, bidder adapter framework, and experimentation system. Responsibilities include designing scalable Go services with strict latency and availability SLAs, evolving bidder adapter framework, improving auction subsystem, strengthening experimentation framework, enhancing observability, driving Azure-native deployment and operational excellence, improving CI/CD, and leading org-wide software delivery initiatives. Required qualifications include a Bachelor's degree in Computer Science or related field with 6+ years engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, and ability to pass Microsoft Cloud background check. Preferred qualifications include a Master's degree or 12+ years experience, deep Go production experience, hands-on OpenRTB/programmatic advertising knowledge, auction system design experience, Kubernetes and Azure production experience, distributed systems expertise, experimentation platform experience, observability skills, and mentoring experience. Salary range is $142,800 - $274,800 per year, higher in SF Bay Area and NYC.
What you'll do
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Mountain View, United States; Redmond, United States
Full-time
Own long-range architecture of MMS platform including OpenRTB request hot path, auction engines, bidder adapter framework, and experimentation system
Drive cross-team technical strategy with peer principals across Microsoft Advertising
Set and enforce engineering standards via design/code reviews, technical RFCs, and mentorship
Identify and resolve systemic risks in reliability, latency, cost, and correctness
Design and build highly scalable Go services with strict latency and availability SLAs
Evolve bidder adapter framework to support new supply types and integration patterns
Improve auction subsystem including pricing, filtration, bidder selection, and response shaping
Strengthen experimentation framework for safe high cadence A/B testing
Improve observability of request path with logging, sampling, metrics, and tracing
Drive Azure-native deployment and operational excellence across multiple Azure services
Lead initiatives to reduce cost-per-request, improve cold-start, config-reload, and cross-region failover
Improve CI/CD processes including canary, progressive rollout, and automated rollback
Lead org-wide initiatives to improve software delivery across full SDLC
Contribute to runbooks, deployment documentation, and oncall readiness
Lead efforts to raise incident response standards and post-incident learning
Leverage AI dev tools to raise team-wide engineering productivity
Requirements
Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements including Microsoft Cloud Background Check
Preferred: Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience OR Bachelor's Degree AND 12+ years experience
6+ years of experience building and operating latency-sensitive backend services with strict SLA requirements
Deep production experience with Go including profiling, GC tuning, concurrency patterns, and performance-sensitive code
Hands-on experience with OpenRTB / programmatic advertising including header bidding, real-time bidding, mediation, exchanges, SSPs/DSPs, brand safety, or identity/cookie syncing
Experience designing or evolving auction systems pricing logic, bidder filtration, dynamic reserve pricing, or floor-price optimization at scale
Production experience with Kubernetes & Azure services including AKS, ACR, Azure Key Vault, Azure Event Hubs, Azure Blob Storage, Azure Application Insights, and Azure DevOps
Solid understanding of distributed systems including consistency trade-offs, fault tolerance, distributed caching, and cross-region replication
Experience designing or scaling experimentation platforms such as A/B testing frameworks, feature flags, or controlled rollout systems
Experience with observability tools including structured logging, high-cardinality metrics, sampling at scale, and event streaming pipelines
Proven record of mentoring senior engineers and driving cross-team technical initiatives
Strong problem-solving skills focused on reliability, observability, and system design
Competitive salary range $142,800 - $274,800 per year (higher range for SF Bay Area and NYC)Potential eligibility for benefits and other compensationInclusive and diverse work cultureOpportunities for mentorship and leadershipUse of AI development tools to enhance productivity
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