Senior Product Manager - AI Platforms and Hybrid Cloud

Lenovo is seeking an experienced Senior Technical Product Manager to shape the roadmap and drive delivery for our enterprise Hybrid Cloud Platform.

In this role, you will define the core capabilities that connect on-premises data centers with public clouds, giving enterprise customers a unified, reliable environment to run and manage their applications. You will focus on what to build and why-defining platform features across compute, storage, networking, and access control that make it easy for engineering teams and enterprise users to deploy workloads wherever they make the most sense.

You will treat both internal offering teams and external enterprise clients as your platform customers. Your mission is to listen to their needs, translate their technical challenges into clear product requirements, and partner with engineering squads who bring the technical architecture to life.

1. Hybrid Cloud Strategy & Core Capabilities

• Define the product vision, roadmap, and release milestones for our hybrid cloud platform across private infrastructure and major public cloud providers.
• Specify core platform features across compute, storage, networking, and user authentication so teams can deploy and run applications seamlessly.
• Lead 0-to-1 MVP scoping for new platform releases, balancing customer-requested features against realistic delivery timelines.

2. Workload Management & Scaling

• Define requirements for workload placement, allowing customers to easily balance applications between their private environments and public cloud capacity.
• Ensure the platform provides reliable multi-tenant isolation, security policies, and health monitoring so customers trust it for production workloads.

3. Developer Experience & Customer Enablement

• Run regular discovery sessions with platform users (both internal teams and external customers) to understand integration friction and day-to-day pain points.
  
• Specify self-service platform tools, clear APIs, and developer documentation that make onboarding smooth and self-guided.
  
• Author clear Product Requirements Documents (PRDs) and user stories that outline business value and acceptance criteria for engineering teams.

4. Cloud Economics & Usage Tracking

• Define capabilities that give customers visibility into their resource usage and spending across hybrid environments.
  
• Specify quota controls, budget alerts, and reporting dashboards so organizations can monitor their cloud investments with confidence.

5. AI & Modern Workload Readiness

• Ensure the platform is ready to support modern workloads, including allocating GPU resources and supporting modern AI tools and data services as customer demand grows.

• 8+ Years of Product Management Experience: Must have a proven track record of owning and shipping software products from concept through launch in a dedicated Product Manager capacity.
  
• Degree in Computer Science, Information Systems, Business, or equivalent practical experience.
• Demonstrated Cloud Offering Ownership: Prior hands-on experience operating as a Product Manager for a commercial or enterprise cloud offering/product (public, private, or hybrid cloud environments).
  
• Cloud & Infrastructure Fundamentals: Solid understanding of core cloud infrastructure components (compute, storage, and networking) and how private enterprise environments connect with public cloud platforms (such as AWS, Azure, or GCP).
  
• Core Inbound PM Craft: Demonstrated experience gathering customer requirements, writing detailed PRDs, defining API interfaces, and prioritizing roadmaps using structured decision-making frameworks.
  
• Customer Empathy & Discovery: Strong background in customer discovery-uncovering underlying user needs and translating them into practical software capabilities.
  
• Communication & Collaboration: Exceptional cross-functional leadership skills, with the ability to bridge business goals with technical conversations and guide engineering squads toward shared outcomes.

• Prior product management experience at an enterprise cloud provider or software infrastructure company.
  
• Working knowledge of container environments (e.g., Kubernetes) or modern cloud deployment models.
  
• Curiosity about modern AI systems and how they utilize cloud and GPU infrastructure.