Microsoft Logo

Microsoft

Principal Software Engineer, Storage Infrastructure

Posted 8 Days Ago
In-Office or Remote
Hiring Remotely in United States
143K-304K Annually
Expert/Leader
In-Office or Remote
Hiring Remotely in United States
143K-304K Annually
Expert/Leader
Design, build, and operate distributed storage and file-system platforms for cloud-scale AI training and inference. Architect storage and caching for Kubernetes and GPU workloads, improve performance, reliability, observability, and resiliency, diagnose cross-layer production issues, and lead architecture reviews. Partner across infrastructure, networking, operating systems, and AI platform teams while mentoring engineers and shaping long-term storage strategy.
The summary above was generated by AI
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

  • 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

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.

Similar Jobs

A Minute Ago
In-Office or Remote
United States
150K-190K Annually
Expert/Leader
150K-190K Annually
Expert/Leader
Digital Media • Fintech • Information Technology • Machine Learning • Financial Services • Cybersecurity • Automation
Serves as the senior technical authority for enterprise browser data protection and security. Owns architecture, roadmap, standards, lifecycle, browser-based DLP controls, integrations, automation, and operational support. Leads complex troubleshooting, major incident response, root-cause analysis, runbook development, and continuous improvement. Partners across cybersecurity, identity, endpoint, network, cloud, risk, compliance, and vendor teams while mentoring engineers and influencing enterprise security design.
Top Skills: Active DirectoryAzure DevopsCasbChrome Enterprise PremiumCisco Secure AccessCloud PlatformsCrowdstrikeCyberarkDigital GuardianDnsEntra IdForcepoint DlpGitGitIslandJAMFMecm/SccmMenlo SecurityMicrosoft Defender XdrMicrosoft Edge For BusinessMicrosoft GraphMicrosoft IntuneMicrosoft Purview DlpMicrosoft SentinelNetskope DlpOktaPalo AltoPalo Alto Prisma BrowserPing IdentityPowershellPythonRest ApisSaseSplunkSwgSymantec DlpTaniumTerraformTls/HttpsVpnZscalerZtna
2 Minutes Ago
In-Office or Remote
United States
155K-200K Annually
Senior level
155K-200K Annually
Senior level
Digital Media • Fintech • Information Technology • Machine Learning • Financial Services • Cybersecurity • Automation
Leads end-to-end marketing strategy and execution for Commercial and Corporate Banking, including client acquisition, retention, product adoption, digital campaigns, ABM, sales enablement, events, analytics, optimization, budgeting, and regulatory governance. Partners with senior banking, sales, data, and digital stakeholders to develop value propositions, integrated marketing plans, and measurable growth initiatives in a regulated B2B financial services environment.
Top Skills: Adobe AnalyticsDemandbaseMicrosoft CopilotExcelMicrosoft PowerpointMicrosoft WordPardotSalesforce
2 Minutes Ago
In-Office or Remote
United States
175K-250K Annually
Expert/Leader
175K-250K Annually
Expert/Leader
Digital Media • Fintech • Information Technology • Machine Learning • Financial Services • Cybersecurity • Automation
Leads enterprise AI tooling and security strategy, building secure cloud-native platforms and protecting AI models, agents, prompts, data, APIs, and outputs. Designs controls for identity, access, encryption, monitoring, threat detection, adversarial testing, governance, and incident response. Provides distinguished technical leadership, mentors engineers, establishes engineering standards, and partners across architecture, security, governance, risk, compliance, and business teams.
Top Skills: AWSBashCircleCIGithub ActionsJenkinsKubernetesLinuxPython

What you need to know about the Charlotte Tech Scene

Ranked among the hottest tech cities in 2024 by CompTIA, Charlotte is quickly cementing its place as a major U.S. tech hub. Home to more than 90,000 tech workers, the city’s ecosystem is primed for continued growth, fueled by billions in annual funding from heavyweights like Microsoft and RevTech Labs, which has created thousands of fintech jobs and made the city a go-to for tech pros looking for their next big opportunity.

Key Facts About Charlotte Tech

  • Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
  • Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
  • Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
  • Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account