This role pays more than
64%
of similar roles. Most pay
$168,500–$235,750
— the shaded band above.
At the midpoint, this role pays about
$209k
versus about
$202k
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
598 open roles
on FindRole.
Listed pay typically runs
$119,800–$234,700
across 586 roles with salary data.
Software Engineer - Compute Infra / HPC will join the Microsoft AI team to build compute infrastructure software that ensures frontier AI systems remain healthy at global scale. The role involves designing and building distributed services, control planes, and platform APIs for the end-to-end lifecycle of AI compute clusters, including provisioning, certification, and automated recovery from hardware or software failures. You will develop foundational primitives such as Kubernetes control planes, networking, and infrastructure-as-code to automate cluster bring-up and fleet health monitoring. Key technologies include Go, Rust, C++, C#, Java, or Python, alongside expertise in Kubernetes, Linux systems, and high-performance interconnects like InfiniBand or RoCE. This position addresses the challenge of transforming raw capacity into secure, observable, and schedulable clusters while replacing manual operational workflows with durable software capabilities to improve researcher velocity and fleet availability.
What does a Software Engineer earn?
Median $197500 from 2196 postings across 133 companies.
Design and build distributed services, control planes, and platform APIs for the end-to-end lifecycle of AI compute clusters.
Develop foundational primitives for cluster bootstrap, Kubernetes control planes, networking, identity, and infrastructure as code.
Automate rack and node qualification, topology validation, and scale testing to reduce cluster bring-up time.
Build a fleet health platform to detect, isolate, and remediate hardware, network, and storage issues automatically.
Create policy-driven automation for the certification, maintenance, and safe rollout of software and infrastructure components.
Translate recurring operational incidents into durable software abstractions and automated guardrails to eliminate manual toil.
Use production evidence, benchmarks, and fault injection to improve system architecture and recovery times.
Provide technical leadership through design reviews, architectural decisions, and mentoring for complex cross-team initiatives.
What we're looking for
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
4+ years of software engineering experience building production distributed systems, infrastructure platforms, or control-plane services.
4+ years of experience designing and implementing scalable software for cloud, datacenter, cluster, or fleet infrastructure using Go, Rust, C++, C#, Java, or Python.
Experience with Kubernetes, Linux systems, public-cloud infrastructure, and infrastructure-as-code or declarative configuration.
Demonstrated ability to debug complex behavior across service, control-plane, operating-system, networking, and hardware boundaries.
Experience leading projects across multiple teams and communicating technical tradeoffs to various stakeholders.
Preferred: Master's degree in Computer Science or a related technical field and 6+ years of experience building distributed systems or infrastructure platforms.
Preferred: Experience with GPU/accelerator systems, high-performance interconnects (InfiniBand, RoCE, RDMA), and low-level Linux system components.
Site Reliability Engineering
Go
Python
Kubernetes
OpenStack
KVM
Terraform
Ansible
Chef
Infrastructure as Code
Unix
Distributed Systems
Bare Metal
VM Orchestration
Automation
Site Reliability Engineering
Go
Python
Kubernetes
Terraform
Ansible
Chef
OpenStack
KVM
Infrastructure as Code
Distributed Systems
Unix
Bare Metal
VM Orchestration
Automation
C++
Python
C
Linux
ARM
PowerPC
x86
TCP
UDP
Machine Learning
Unit Testing
Hardware-in-the-loop
Computer Architecture
Networking Protocols
Performance Optimization