Senior Principal Product Development Manager

Senior Principal Product Development Manager (Commercial Notebook)

Product Development Management is a fast-paced environment where innovative thinking is prized. Our team focuses on the delivery of products or computer-based systems for external customers. We lead and deliver the entire lifecycle from product definition and planning through to production and release. We also oversee modifications, upgrades and maintenance of the product or product line. And to make the whole process run smoothly and seamlessly, we’re experts in project management, from initiation through to delivery, and liaise with other departments on technical matters.

Join us to do the best work of your career and make a profound social impact as aSenior Principal Product Development Manager on ourProduct Development Management Team inTaipei

What you’ll achieve

As a Senior Principal Product Development Manager, you will lead high-complexity products and platforms through the entire product lifecycle while driving engineering modernization across the organization. You will establish scalable development frameworks, enable data-driven decision making, and accelerate adoption of AI and intelligent automation to improve development efficiency, quality, and execution predictability.

You will play a key leadership role in transforming product development practices through data standardization, process centralization, and Agentic AI-enabled workflows that enhance engineering productivity and business outcomes.


You will:

• Define and continuously improve product and solution development lifecycle processes across the organization. Lead high-complexity NPI and sustaining programs from concept through GA and lifecycle management. Drive program governance, release readiness, and execution excellence. Ensure dependency management, deliverable tracking, and cross-functional execution alignment across products, platforms, and organizations.
• Data Standardization & Centralization
  •    Establish engineering data standards, governance models, and best practices across product development organizations.
  •    Drive centralization of engineering knowledge, project artifacts, development metrics, and product lifecycle data.
  •    Build a scalable data foundation that enables analytics, automation, and AI-driven decision making.
  •    Improve data quality, traceability, accessibility, and reusability across development functions.
• Engineering Modernization & Transformation
  •    Lead engineering modernization initiatives that simplify workflows, eliminate inefficiencies, and improve execution velocity.
  •    Drive digital transformation programs across product development organizations.
  •    Identify opportunities to streamline processes through automation, workflow integration, and advanced analytics.
  •    Define and execute modernization roadmaps aligned with business and engineering objectives.
• AI & Agentic AI Enablement
  •    Champion AI-first engineering practices across product development organizations.
  •    Evaluate, deploy, and scale AI-enabled solutions to improve engineering productivity, quality, and decision making.
  •    Identify opportunities for Agentic AI to support:
  o    Program management
  o    Engineering documentation
  o    Requirements management
  o    Risk assessment
  o    Issue triage
  o    Knowledge discovery
  o    Design review processes
  •    Partner with engineering, architecture, and IT teams to establish AI-enabled development ecosystems.
  •    Ensure responsible adoption of AI technologies through appropriate governance, security, and compliance practices.
• Risk Management & Operational Excellence
  •    Define program risk management strategies and drive mitigation plans across organizations.
  •    Establish predictive risk identification mechanisms leveraging engineering metrics, analytics, and AI insights.
  •    Drive consistent and accurate cross-functional metrics and operational reviews.
  •    Shape technical and operational goals that support business priorities and long-term organizational transformation
   

Take the first step towards your dream career
Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:

Essential Requirements

• 12 to 15 years of related experience in a professional role. Excellent knowledge and application of engineering concepts along with effective problem-solving ability
• Solid understanding of business environment and competition
• Ability to manage, motivate and direct a cross functional workgroup and drive successful negotiations
• Solid interpersonal and presentation skills
• AI & Transformation Capabilities
  •    Demonstrated AI mindset with the ability to identify opportunities for AI-enabled productivity improvements.
  •    Experience leveraging AI-assisted tools and automation solutions to improve engineering efficiency and execution effectiveness.
  •    Understanding of data standardization, knowledge management, and information governance principles.
  •    Ability to lead modernization initiatives involving process transformation, workflow automation, and digital enablement.
   

Desirable Requirements

• Bachelor's degree in Engineering, Computer Science, Data Science, or related field. Master's degree preferred.
• Experience with AI-assisted development platforms, Generative AI technologies, Agentic AI frameworks, or intelligent automation solutions. 
• Experience building centralized engineering data foundations, knowledge management systems, or enterprise workflow platforms.
• Experience leading large-scale engineering transformation or modernization initiatives.
• Familiarity with analytics platforms, automation frameworks, Power Platform, Python, AI copilots, or similar technologies.
   
• Additional Future-Ready Leadership Expectations
  •    Foster an AI-first and data-driven culture across engineering organizations.
  •    Drive adoption of standardized and centralized development practices.
  •    Enable scalable engineering operations through intelligent automation and Agentic AI.
  •    Improve development cycle time, product quality, execution predictability, and engineering productivity.
  •    Build the organizational foundation necessary for next-generation AI-powered product development ecosystems.