This role pays more than
61%
of similar roles. Most pay
$174,600–$232,187
— the shaded band above.
At the midpoint, this role pays about
$209k
versus about
$203k
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.
As a Principal Supercomputing Operations Software Engineer within the Artificial Intelligence and High Performance Computing organization, you will serve as the technical authority for InfiniBand and GPU interconnect fabric operations across large-scale AI supercomputing environments. You will manage high-severity incidents, perform multi-layer systems debugging across Subnet Manager, PCIe, firmware, drivers, and OS layers, and develop systemic prevention mechanisms to ensure training stability and SLA compliance. The role involves architecting automation, telemetry, and diagnostic tools to improve the observability of interconnect fabrics while authoring authoritative playbooks and escalation models. You will utilize skills in C, C++, C#, Java, JavaScript, or Python to solve complex reliability issues within high-performance computing infrastructure. Your work directly addresses the challenge of maintaining reliable, performant interconnect fabrics for frontier AI training and large-scale distributed simulations at scale.
Serve as the technical authority for InfiniBand and GPU interconnect fabric operations across large-scale AI supercomputing environments.
Lead and orchestrate high-severity fabric incidents including detection, triage, mitigation, recovery, and root cause analysis.
Perform multi-layer systems debugging across InfiniBand, Subnet Manager, PCIe, firmware, drivers, and OS layers.
Identify recurring failure patterns to define reliability models and systemic prevention mechanisms at fleet scale.
Author authoritative technical support guides, playbooks, and escalation frameworks for use across the organization.
Architect and develop automation, telemetry, and diagnostic tools to improve observability and mean time to mitigation.
Influence engineering direction by setting operational standards and partnering with hardware and firmware teams.
What we're looking for
Bachelor's Degree in Computer Science or related technical field and 6+ years of experience coding in languages like C, C++, C#, Java, JavaScript, or Python (or equivalent).
Ability to pass the Microsoft Cloud Background Check.
6+ years of experience operating large-scale distributed systems, high-performance computing (HPC), or artificial intelligence (AI) infrastructure in production environments (preferred).
Demonstrated ownership of mission-critical production infrastructure with direct impact on service availability, GPU workloads, and customer SLAs (preferred).
Strong Linux systems knowledge with experience debugging low-level infrastructure issues across operating systems, drivers, and services (preferred).
Proven ability to reason across hardware, firmware, drivers, and software stacks to diagnose and resolve complex production issues (preferred).
Bachelor's Degree in Computer Science or related field and 10+ years of engineering experience, OR a Master's Degree and 8+ years of experience (preferred).
Kubernetes
Go
Rust
C++
C#
Python
Terraform
Infrastructure as Code
Distributed Systems
Linux
Azure
InfiniBand
RoCE
RDMA
NVLink
NCCL
Bare-metal Provisioning
Container Runtimes
C++
Python
C
Linux
ARM
PowerPC
x86
TCP
UDP
Machine Learning
Unit Testing
Hardware-in-the-loop
Computer Architecture
Networking Protocols
Performance Optimization
GPU
CUDA
Machine Learning
Deep Learning
High-Performance Computing
Generative AI
Agentic AI
Docker
Kubernetes
Slurm
GPGPU
Parallel Computing
Data Science
Networking