Product Manager – AI Software and Solution

Job Description

We are seeking a visionary, strategic, and technically deep Senior Product Manager to define, build, and scale our Data Center AI Software Portfolio. In this role, you will be the primary strategist and execution leader driving end-customer-facing software solutions for Intel's high-growth Data Center accelerator products.

Job Description:

We are seeking a visionary, strategic, and technically deep Senior Product Manager to define, build, and scale our Data Center AI Software Portfolio. In this role, you will be the primary strategist and execution leader driving end-customer-facing software solutions for Intel's high-growth Data Center accelerator products.

You will lead the end-to-end product strategy for our generative AI software stack, with a specific focus on use-case-driven Agentic toolkits, containerized microservices, and enterprise-grade, ready-to-deploy (turnkey) solutions. Your mission is to democratize high-performance accelerated computing by removing the complexities of AI deployment, establishing a robust developer ecosystem, and creating highly competitive, open-standards-based software offerings that challenge industry incumbents.

• Portfolio Strategy and Roadmap Ownership
• Define and Scale:
  Own the product lifecycle, strategic vision, and execution roadmap for Intel's Data Center AI Software and customer experiences.
• Turnkey Solutions:
  Drive the definition and productization of enterprise-ready, out-of-the-box (OOTB) software solutions (cloud, hybrid, and on-premises) that enable seamless AI deployment.
• Agentic and Microservices Ecosystem:
  Lead the strategy for modular AI software architectures, focusing on industry compliant microservices, Hetro frameworks, and Agentic AI toolkits.
• Competitive Positioning and Market Intelligence
• Market Disruption:
  Maintain deep, continuous analysis of competitor hardware/software stacks to identify market whitespace, software gaps, and unique value-proposition vectors for Intel's hardware.
• GTM:
  Collaborate with Product Marketing and Business Development to establish competitive software offering, licensing, and product packages that drive high volume adoption.
• Developer and Partner Enablement
• Ecosystem Growth:
  Foster strong relationships with Cloud Service Providers (CSPs), emerging Neoclouds, Independent Software Vendors (ISVs), and the open-source AI community (Hugging Face, PyTorch, Lang Chain, etc.).
• Turnkey Blueprints:
  Deliver developer-friendly reference architectures, deployment blueprints (Docker Compose, Kubernetes Helm Charts, and Terraform), and system telemetry integrations.
• Frictionless Onboarding:
  Work closely with the technical documentation and developer relation teams to ensure APIs, SDKs, and toolkits are exceptionally well-documented and simple to adopt.
• Cross-Functional Collaboration
• Engineering Alignment:
  Partner intimately with software engineering, AI researchers, and silicon architecture teams to translate complex customer challenges into clear PRDs (Product Requirement Documents) and engineering backlogs.
• Shift-Left Methodologies:
  Coordinate with simulators, emulation, and validation teams to ensure software readiness prior to hardware tap-out.

• Education:
  
  Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a highly technical quantitative discipline. (An MBA or advanced technical degree is highly preferred).
• Experience:
  
  10+ years of product management, product engineering, or technical marketing experience in the data center, cloud-native, or enterprise software domain.
• AI/ML Technical Domain Expertise: 3+ years of dedicated product leadership within deep learning, LLMs, generative AI stacks, or accelerated computing.
• Cloud-Native Proficiency:
  Practical understanding of cloud-native orchestration tools (Kubernetes, Red Hat Open Shift), containerization (Docker), and modern microservice mesh architectures.

• AI Software Knowledge:
  Direct experience with GPU software stack from middleware to frameworks to Agentic toolkits.
• AI System Design:
  Proven track record of productizing RAG applications, Agentic AI, vector databases (e.g., Milvus, Redis, Qdrant), or complex AI orchestration frameworks.
• Enterprise Software Delivery:
  Experience working with AI Inference deployment and Agentic frameworks is highly desirable
• Thriving in Ambiguity:
  Ability to successfully manage multiple complex, matrixed work streams and drive alignment among…