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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 644 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 624 roles with salary data.

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TL;DR · Principal Software Engineer

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As a Principal Software Engineer, you will join the team driving the next generation of Azure Kubernetes Service and Azure Storage platforms. You will lead the architecture and evolution of large-scale infrastructure, including distributed systems, machine learning infrastructure, model serving, training platforms, observability, and platform engineering. Your daily responsibilities involve defining technical direction for cloud infrastructure, designing distributed systems for data processing, improving compute utilization, and supporting MLOps practices for model lifecycle management. You will work with various teams to ensure reliability, security, and scalability for AI workloads in production environments. The role requires proficiency in languages such as Go, C, C++, C#, Java, JavaScript, or Python, along with expertise in Kubernetes, containers, networking, storage systems, site reliability engineering, and large-scale distributed systems to solve complex cloud platform challenges.

What does a Software Engineer earn in Remote?

Median $202482 from 350 postings across 56 companies.

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Skills

Azure Kubernetes Go Python C++ C# Java JavaScript Distributed Systems MLOps KubeRay Kueue Cloud Infrastructure Site Reliability Engineering Containers Model Serving Data Processing Observability

What you'll do

Define technical direction for cloud infrastructure and machine learning platforms across multiple engineering teams.
Design and review distributed systems for model training, inference, data processing, and platform services.
Align architecture, reliability, security, and scalability requirements with partner engineering and product teams.
Improve platform efficiency regarding compute utilization, resource management, and service performance.
Support MLOps practices for the development, deployment, monitoring, and lifecycle management of models.
Provide technical guidance for Kubernetes-based platforms and AI workloads in production environments.
Establish long-term platform planning, technical standards, and engineering best practices across the organization.

What we're looking for

Bachelor's Degree in Computer Science or related field and 6+ years of technical engineering experience in languages like Go, C, C++, C#, Java, JavaScript, or Python.
Ability to pass the Microsoft Cloud Background Check every two years.
Master's Degree in Computer Science or related field and 8+ years of technical engineering experience (preferred).
Bachelor's Degree in Computer Science or related field and 12+ years of technical engineering experience (preferred).
Deep experience with Kubernetes, containers, cloud platforms, networking, storage systems, site reliability engineering, and large-scale distributed systems (preferred).
Experience designing and operating machine learning platforms, model training environments, GPU infrastructure, and MLOps frameworks (preferred).
Strong understanding of modern large language model ecosystems including training, inference, model serving, and observability (preferred).
Demonstrated ability to lead architecture decisions and drive technical strategy across cross-functional engineering teams (preferred).