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Principal Software Engineer, Storage Infrastructure

  • $142k – $274k
  • |
    Redmond
  • |12 years of exp
  • |Full Time
Posted: 2 weeks ago• Recruiter recently active
Job Location
Redmond
Remote Work Policy

In office

Visa Sponsorship

Not Available

RelocationAllowed
Skills
Python
C++
Java
Javascript
Networking
C#
Performance
Databases
Distributed Systems
Infrastructure
C
High Availability
Software
Replication
Consistency
Reliability
File Systems
Disaster Recovery
Kubernetes
Storage Systems
Business Continuity
Durability
AI Training
Inference
LLM Inference
Technical Design Reviews
Cloud Infrastructure Services
Distributed Storage Systems
Platform Components
Fault-Tolerant Services
Regional Failover
Troubleshooting Complex Distributed-System Failures
Cross-Team Engineering Projects
Geo-Distributed Storage Architectures
Large-Scale Kubernetes Clusters
High-Performance Caching
Key-Value KV Caching

About the job

Overview

The Foundry and Inference Training (FIT) team within Microsoft AI Infrastructure builds the platforms, systems, and operating mechanisms that enable teams to develop, train, deploy, and run AI services at scale.

The FIT Infrastructure team builds storage and accelerated-compute platforms for large-scale AI training and inference on Azure. You will work across distributed storage, Kubernetes, GPU clusters, networking, and cloud-scale systems to deliver secure, reliable, high-performance, and cost-efficient infrastructure.

As a Principal Software Engineer, Storage Infrastructure, you will design, build, and operate storage platforms for foundation-model pre-training, post-training, fine-tuning, and inference. You will partner with Azure infrastructure, networking, operating systems, and AI platform teams to solve challenging problems in storage performance, reliability, scalability, and developer productivity. This role offers opportunities to shape platform architecture, deepen expertise in distributed systems, and grow your technical leadership through broad cross-team impact.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world.

Responsibilities

Responsibilities:

  • Design, build, and evolve distributed storage systems and file systems for cloud-scale AI training and inference workloads.
  • Architect and operationalize storage stacks for large Kubernetes clusters, optimizing data access, throughput, latency, scalability, and reliability for GPU-accelerated workloads.
  • Design storage and KVkey-value caching architectures that improve LLM inference latency, throughput, resource utilization, and cost efficiency.
  • Improve durability, availability, performance, and operational maturity through automation, observability, diagnostics, incident response, and resiliency engineering.
  • Analyze complex cross-layer production issues, identify root causes, and implement durable improvements across storage, compute, networking, and runtime components.
  • Partner with infrastructure and machine learningLLM platform teams to deliver end-to-end capabilities for foundation-model pre-training, post-training, fine-tuning, and inference.
  • Lead architecture reviews, influence long-term storage strategy, mentor engineers, and establish engineering practices for secure and reliable cloud services.
  • Embody our Culture and Values

Qualifications

Required/minimum qualifications

  • Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

  • OR equivalent experience.

Other Requirements

Additional Or Preferred Qualifications

  • Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Additional or preferred qualifications

  • Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

  • OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

  • OR equivalent experience.

  • 5+ years of experience designing, building, or operating distributed systems, storage systems, file systems, databases, or cloud infrastructure services.

  • Experience operating highly available, fault-tolerant services in production environments, including troubleshooting complex distributed-system failures.

  • Experience applying storage concepts such as durability, replication, consistency, performance, and reliability to production system design.

  • Experience leading technical design reviews or delivering cross-team engineering projects across software, infrastructure, networking, or platform components.

  • Experience with geo-distributed storage architectures, replication, disaster recovery, business continuity, or regional failover.

  • Experience designing storage platforms for large-scale Kubernetes clusters supporting AI training or inference.

  • Experience with high-performance caching or key-value KV caching for LLM inference.

  • Familiarity with distributed training or inference technologies, including collective communication libraries and model, data, or pipeline parallelism.

  • Familiarity with high-throughput networking and low-latency communication technologies such as Remote Direct Memory Access (RDMA), InfiniBand, or RDMA over Converged Ethernet (RoCE).

  • Familiarity with GPU-accelerated environments, including CUDA, GPU drivers, Kubernetes device plugins, or container runtime integration.

  • Experience using machine learning or AI techniques for anomaly detection, forecasting, incident management, capacity planning, or operational automation.

#AIINFRA

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

About the company

Microsoft company logo

Microsoft

Actively Hiring
More jobs
Help People and Businesses Throughout the World Realize Their Full Potential5000+ Employees
Company Location
Redmond
Company Size
5000+
Company Type
VC Firm
  • B2C
  • B2B
  • Public Stage
    Publicly traded company
Learn more about Microsoft image

Funding

AMOUNT RAISED
Undisclosed amount
FUNDED OVER
1 round
Round
IPO
Undisclosed amount
IPO - Mar 1986

Perks

Industry leading healthcare
Maternity and paternity leave
Generous time away
Giving programs
Discounts on products and services
Educational Resources
Opportunities to network and connect
Savings and Investments

Founders

Adam Menges
Lobe
San Francisco
image
Phung Huynh Ngoc
Founder
image
Sergey Yaroslav
Lead Developer • 18 years
Auckland
image
View the team image