Director of Product Management – AI Essentials

About the role

This role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office.

Job Description

The Director of Product Management, AI Essentials is responsible for defining and driving the strategy, development, and execution of AI-powered software solutions within the organization’s broader product portfolio. This individual will lead end-to-end product initiatives, partnering closely with engineering, architecture, and go-to-market teams to deliver scalable solutions that address real customer needs. The role requires a strong understanding of modern AI technologies and their practical application, along with the ability to translate complex concepts into clear product direction. This is a high-impact opportunity to shape a rapidly growing area of the business and help bring innovative AI capabilities to market.

Responsibilities

• Own end to end strategy, roadmap, and delivery of HPE's enterprise AI software platform across all deployment models
• Drive modular platform architecture spanning production inference, agent deployment, GenAI workflows, and edge AI
• Define and execute GTM strategy targeting new buyer personas (data science, MLOps, AI platform teams)
• Build monetization and packaging strategy across modular software offerings
• Align cross functionally with Private Cloud, Edge, and GreenLake Platform teams
• Deliver executive ready materials and reviews with minimal iteration
• Provide guiding principles for and define value proposition, customer segmentation, and business case to bring innovative and disruptive business unit products to the market (i.e. Product configuration mix, Revenue/margins, financials, market share)
• Drive integration of the product portfolios lifecycles to business unit goals across all phases of the product portfolio and business unit lifecycle (e.g. planning, development, launch, management, exit)

Education And Experience Required

• Bachelor's degree or equivalent in computer science, engineering or related field of study
• MBA or advanced degree in computer science or engineering preferred
• 15+ years of work experience in product management or related field
• 5+ years of progressive product management leadership in AI/ML, data infrastructure, and/or data science domains
• Experience building or scaling AI/ML platforms targeting data science and MLOps personas
• Track record of taking software products from early stage to meaningful revenue
• Deep familiarity with inference, model serving, agent frameworks, and GPU ecosystem
• Demonstrated daily use of AI tools in professional workflow

Knowledge And Skills

• AI/ML Platform Expertise: Proven experience in inference operations, model lifecycle management, agent frameworks, GPU scheduling, and the enterprise AI toolchain.
• Software Product Management: Experience building and scaling enterprise software platforms with clear packaging, pricing, and adoption motions. Understands SaaS and platform business models.
• AI Native Product Leadership: Uses AI tools daily to accelerate strategy, analysis, and communication. Designs products with AI as a core capability.
• Executive Communication and Presence: Produces decision oriented materials for senior leadership with minimal revision. Engages credibly in executive forums without extensive pre wires.
• New Market Development: Experience reaching new buyer personas and building GTM motions into technical communities (data science, MLOps, DevOps). Understands how to land with developers and scale to enterprise buyers.
• Broad Technical Depth: Systems level understanding across AI/ML, cloud platforms, infrastructure, and security. Sees broadly across products and GTM. Uses AI to go deeper as needed.
• Cross Functional Leadership: Aligns engineering, GTM, and operations in a matrixed environment. Forces decisions and builds credibility quickly.
• Commercial Acumen: Connects product decisions to revenue, pricing, and competitive positioning. Understands how to build a software monetization engine.
• Technical SME: Understanding and knowledge of the relevant industry and ability to provide product specific technical training to the team.