Principal Software Architect

• Define and own end-to-end architecture for complex AI-enabled software platforms across client applications, backend services, cloud workflows, local device interactions, connected hardware, and enterprise integrations
• Establish architectural principles, system boundaries, design patterns, and technology choices for scalable, secure, reliable, maintainable, high-performance, and extensible platforms
• Lead architecture of AI/ML capabilities including generative AI, LLM and agentic workflows, retrieval-augmented generation, embeddings, model orchestration, inference services, machine learning, and edge AI execution
• Design production-ready AI/ML systems with evaluation, experimentation, model and prompt versioning, telemetry, monitoring, feedback loops, responsible AI, safety controls, and operational governance
• Align architecture across local applications, cloud services, enterprise identity, device management platforms, connected devices, firmware-adjacent interfaces, and backend systems
• Define and address security, privacy, compliance, performance, resiliency, auditability, manageability, diagnostics, deployment readiness, and supportability requirements
• Maintain hands-on technical engagement through prototyping, architecture and code reviews, technical investigations, performance analysis, and resolution of high-impact engineering challenges
• Guide senior engineers and technical leads, raising standards for architecture, code quality, testing, design documentation, technical decision-making, and software lifecycle practices
• Produce and maintain architecture artifacts including system diagrams, architecture decision records, integration specifications, technical roadmaps, risk assessments, and platform evolution plans
• Evaluate emerging technologies, AI/ML frameworks, cloud services, and enterprise platforms
• Influence executive and cross-functional stakeholders by communicating technical strategy, trade-offs, risks, dependencies, technical debt, and investment priorities
• Work directly with customers to understand real-world needs and incorporate feedback into product and technical direction
• Shape an incubation effort within HP’s PC ecosystem and architect edge AI-enabled experiences for intelligent PCs and peripherals
• Partner with software engineering, UX, product management, hardware engineering, security, manageability, validation, DevOps, systems engineering, and executive stakeholders

Requirements

• Bachelor’s or Master’s degree/PhD in Computer Science, Software Engineering, Computer Engineering, or Electrical Engineering
• 10+ years of software engineering experience
• Significant experience designing and delivering complex software platforms, distributed systems, enterprise applications, cloud-connected products, or device-integrated software solutions
• 5+ years of experience in a technical leadership, architecture, principal engineer, staff engineer, or equivalent role
• Deep experience designing end-to-end software architectures spanning frontend applications, backend services, desktop applications, cloud platforms, APIs, data systems, device interfaces, and enterprise integrations
• Strong technical depth in frontend technologies such as Angular, React, TypeScript, JavaScript, HTML, and CSS
• Strong backend and systems development experience with C++, Rust, Python, C#, Node.js, Go, or similar
• Experience with LLMs, Vision Language, and speech models
• Experience defining architecture for Windows desktop applications, companion applications, background services, system tray applications, OS-integrated applications, or software interacting with local system services
• Hands-on experience with PyTorch, TensorFlow, ONNX Runtime, or similar AI/ML frameworks and runtimes
• Understanding of edge AI, model compression, quantization, hardware acceleration, latency, memory and compute constraints, and hybrid edge-cloud execution
• Strong understanding of distributed systems, API design, service-oriented and event-driven architectures, asynchronous processing, messaging, caching, fault tolerance, and application state management
• Experience with AI service integration, LLM APIs, prompt workflows, model orchestration, embeddings, inference APIs, evaluation pipelines, and responsible AI practices
• Experience integrating local software with cloud services, backend systems, enterprise identity providers, device management platforms, and enterprise software ecosystems
• Strong understanding of software security, privacy, authentication, authorization, compliance, audit logging, data protection, and enterprise governance
• Experience with Git-based workflows, CI/CD pipelines, automated testing, release engineering, and production support
• Preferred: Tauri, WebView, WebRTC, COM interfaces, PowerShell automation, native application integration, or cross-platform desktop frameworks
• Preferred: Microsoft Graph, Microsoft Intune, Azure services, enterprise APIs, identity platforms, SSO, device management, and manageability workflows
• Preferred: MS Intune, ADMX/Group Policy, HP WXP, or similar MDM/UEM platforms
• Preferred: connected-device software, peripheral integration, local device discovery, firmware-adjacent workflows, or hardware/software co-design
• Preferred: incubation products, proof-of-concept platforms, beta programs, early-stage software initiatives, or new product introductions
• Willingness to travel 25%

Core Competencies

Demonstrates expertise in defining and owning end-to-end architecture for AI-enabled software platforms, with a strong focus on scalable, secure, and maintainable systems. Proficient in leading technical teams and guiding architectural decisions across complex software ecosystems, ensuring alignment with business needs and compliance standards.

Highest-signal resume keywords

• AI/ML Architecture Design
• Frontend Technologies: Angular, React, TypeScript
• Backend Development: C++, Python, Node.js
• Cloud Services Integration
• Software Security and Compliance

ATS Optimization Keywords

Hard Skills

• AI/ML Frameworks: PyTorch, TensorFlow
• Distributed Systems Design
• API Design and Integration
• Model Orchestration and Inference
• Edge AI Execution
• Software Architecture Principles
• Version Control: Git
• CI/CD Pipelines
• Performance Analysis
• Technical Documentation

Soft Skills

• Technical Leadership
• Cross-Functional Collaboration
• Stakeholder Communication
• Problem Solving
• Mentoring

Certifications & Qualifications

• Bachelor’s or Master’s Degree in Computer Science
• PhD in Computer Science or Related Field

Industry Keywords

• AI-Enabled Software Platforms
• Enterprise Applications
• Device Management
• Compliance Standards
• Connected Devices

Tools & Technologies

• Azure Services
• Microsoft Graph
• DevOps Tools
• Automated Testing Frameworks
• Cloud Platforms