This role pays more than
95%
of similar roles. Most pay
$152,150–$207,350
— the shaded band above.
At the midpoint, this role pays about
$216k
versus about
$180k
for comparable roles.
Based on 239 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
1580 open roles
on FindRole.
Listed pay typically runs
$119,800–$234,700
across 1408 roles with salary data.
The Segment CTO role within Microsoft’s U.S. Public Sector Industries (USPSI) Office of the Chief Technology Officer (OCTO) is a senior-level position focused on driving mission-critical technology initiatives for Federal, State and Local Governments and Education (SLED), and the Defense Industrial Base (DIB). This individual will lead executive technical leadership by advising CTOs and other high-ranking officials on architecture strategy, including Zero Trust adoption and cyber-resilient data ecosystems. They will also define secure reference architectures to support complex operational environments and influence product development through field-derived challenges. The ideal candidate has extensive experience in technology management, consulting, policy, and legal/privacy domains, with a strong background in cloud security and AI transformation. Proficiency in areas such as Azure, Kubernetes, and DevSecOps is essential, along with expertise in regulatory compliance and cross-cloud observability. This role demands deep understanding of SLED’s unique technical challenges and the ability to navigate complex, high-stakes environments to deliver impactful solutions at scale.
UPS
Generator
AHU
Servers
SANs
Networking
Rack/Enclosures
Structured Cabling
CompTIA
ITIL v3 Foundation
MOF Certifications
PMP
CDCP
CCNA Certifications
ASICS/Inventory Control
Leadership Development Certificates
CUDA
GPU
ROCm
Triton
PTX
CUTLASS
C++
Parallel Computing
Algorithm Optimization
Performance Profiling
Memory Hierarchies
Deep Learning
Model Compression
Accelerator Design
Machine Learning
Systems Research