Principal Software Engineer | Microsoft Careers

Microsoft

Quick summary

Work type: On-site
Location: —
Salary: $163,000–$296,400 / yr
Posted: 140 days ago
Closes: Jul 21, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $191k

This role $230k

$121k most similar roles pay here $315k

This role pays more than 83% of similar roles. Most pay $174,037–$208,800 — the shaded band above. At the midpoint, this role pays about $230k versus about $191k for comparable roles.

Based on 240 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 1103 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 985 roles with salary data.

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At a glance

TL;DR · Principal Software Engineer | Microsoft Careers

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As a Principal Software Engineer on the HPC/AI team, you will lead the development of next-generation networking infrastructure for AI training and inference within Azure Cloud. Your responsibilities include partnering with stakeholders to define user requirements, designing high-performance communication frameworks, and optimizing networking solutions for large-scale AI systems. You will also benchmark and enhance the scalability and reliability of these systems, debug complex issues in high-performance environments, and act as a Designated Responsible Individual (DRI) to monitor system health and initiate restorative actions. The role requires hands-on experience with AI-specific hardware like InfiniBand and ROCE, expertise in networking protocols such as Ethernet and TCP/IP, and familiarity with network virtualization and observability tools for large-scale monitoring. Additionally, you should have a background in building scalable and fault-tolerant systems in distributed environments.

Skills

Azure InfiniBand ROCE NVLink Ethernet TCP/IP RDMA gRPC SDN GPUs TPUs Telemetry Observability Docker Kubernetes CI/CD Prometheus Grafana

What you'll do

Lead the design and development of high-performance networking solutions for AI training.
Optimize communication frameworks to ensure low-latency and low-jitter performance.
Enhance scalability and reliability of petabyte-scale data transfer systems.
Debug complex networking issues in large-scale, high-performance environments.
Act as Designated Responsible Individual (DRI) for system monitoring and maintenance.

What we're looking for

Extensive experience with AI-specific hardware networking technologies.
Deep understanding of networking protocols and distributed system architectures.
Proficiency in software-defined networking (SDN) and network performance tuning.
Expertise in working with AI accelerators like GPUs and TPUs.
Hands-on experience with telemetry and observability tools for large-scale monitoring.
Background in building scalable, fault-tolerant systems in distributed environments.
Proactive approach to learning new AI trends and technical solutions.