HP
Principal Software Architect
$165K–$260K
Spring, Texas, United States of America +1 · Principal · Full-time · Posted Sep 11, 2026
- Location
- Spring, Texas, United States of America
Palo Alto, California, United States of America - Experience
- 10+ years of software engineering experience; 5+ years in technical leadership, architecture, principal engineer, staff engineer, or equivalent roles.
- Education
- Bachelor’s or Master’s degree/ PhD in Computer Science, Software Engineering, Computer Engineering, or Electrical Engineering.
About the job
Defines and guides architecture for HP’s AI-enabled software platforms, including intelligent PC and peripheral experiences spanning device, client, cloud, and enterprise systems.
What you'll do
- Own end-to-end platform architecture and establish design principles, system boundaries, and technology choices.
- Lead production AI/ML architecture, including evaluation, monitoring, safety, and edge execution.
- Guide engineering teams and communicate technical strategy, risks, and roadmaps to cross-functional and executive stakeholders.
What they ask for
- Bachelor’s, Master’s, or PhD in Computer Science, Software Engineering, Computer Engineering, or Electrical Engineering.
- 10+ years of software engineering experience designing and delivering complex software platforms or related systems.
- 5+ years in technical leadership, architecture, principal engineer, staff engineer, or an equivalent role.
- Experience with end-to-end software architecture, AI/ML integration and deployment, distributed systems, and security.
Nice to have
- Experience with Tauri, WebView, WebRTC, COM interfaces, PowerShell, or cross-platform desktop frameworks.
- Experience with Microsoft Graph, Microsoft Intune, Azure services, enterprise identity, or device management.
Pay
$165,450 to $259,750 USD annually (base salary)
Tools
Angular, React, TypeScript, C++, Rust, Python, PyTorch, TensorFlow
AI focus
Architects and delivers production AI/ML capabilities, including generative AI, LLM and agentic workflows, retrieval-augmented generation, embeddings, inference, and edge AI; defines evaluation, monitoring, safety, and governance practices.
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