Microsoft
Principal Software Engineer, AI Infrastructure
$143K–$304K
Redmond, WA · On-site · Principal · Full-time · Posted Oct 16, 2026
- Experience
- Required: 6+ years building distributed systems. Preferred: Master's Degree plus 8+ years, or Bachelor's Degree plus 12+ years, or equivalent experience; additional preferred experience includes 5+ years on public cloud platforms and 3+ years with routing, scheduling, or resource optimization systems.
- Education
- Bachelor's Degree in Computer Science or related technical field, or equivalent experience.
About the job
Designs and operates distributed systems that route and prioritize AI traffic and allocate computing capacity across Microsoft's global infrastructure.
What you'll do
- Own system design for managing AI traffic and compute capacity across regions; guide design reviews.
- Build and review code for routing, prioritization, and capacity planning; deliver changes through gradual rollouts and feature flags.
- Lead reliability and incident work, partner with product and infrastructure teams, and mentor engineers.
What they ask for
- Bachelor's Degree in Computer Science or related technical field, or equivalent experience.
- 6+ years technical engineering experience building distributed systems, coding in C#, Java, Go, or other languages.
- Meet Microsoft, customer and/or government security screening requirements, including the Microsoft Cloud Background Check.
Nice to have
- Experience with public cloud, traffic routing or scheduling, resource optimization, AI/ML infrastructure, or highly available services.
- Experience with Python, Docker, and Kubernetes; or leading projects across 3 or more partner teams.
Pay
USD $142,800 - $274,800 per year (base salary); USD $188,000 - $304,200 per year (base salary)
Tools
C#, Java, Go, Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), Python, Docker
AI focus
Builds infrastructure to route and prioritize AI requests and allocate GPU capacity. Also helps use AI tools and agents across the software development lifecycle, following Responsible AI practices.
Model-written summary · the original posting is authoritative