Product Director - AI Infrastructure Platforms

Ignite your passion for product innovation by leading customer-centric development, inspiring solutions, and shaping the future with your strategic vision and influence.

As a Product Director in AI Infrastructure Platforms you lead innovation through the development of products and features that delight customers. As a leader on the team, you leverage your advanced capabilities to challenge traditional approaches, remove barriers to success, and foster a culture of continuous innovation that helps inspire cross-functional teams create groundbreaking solutions that address customer needs. you will set the vision, strategy, and direction for the platform's inferencing product area.

The platform is an integrated suite of specialized AI infrastructure for model training, inference, and experimentation—consisting of compute, storage, network, and management services—with offerings that span public cloud, on-premises, Neo Cloud, and edge. You will define and deliver the go-to-market strategy, drive platform adoption across lines of business, and advance product capabilities toward an enterprise-scale AI Factory. Success in this role requires navigating rapid AI hardware evolution, complex multi-vendor ecosystems, and the regulatory demands of a highly regulated global financial institution—delivering infrastructure for high-value AI use cases.

• Oversees the product roadmap, vision, development, execution, risk management, and business growth targets
• Leads the entire product life cycle through planning, execution, and future development by continuously adapting, developing new products and methodologies, managing risks, and achieving business targets like cost, features, reusability, and reliability to support growth
• Coaches and mentors the product team on best practices, such as solution generation, market research, storyboarding, mind-mapping, prototyping methods, product adoption strategies, and product delivery, enabling them to effectively deliver on objectives
• Owns product performance and is accountable for investing in enhancements to achieve business objectives
• Monitors market trends, conducts competitive analysis, and identifies opportunities for product differentiation
• Own the product area vision, strategy, roadmap, execution, and business growth targets, with a strategic mandate to mature the platform toward an enterprise-scale AI Factory
• Maximize returns on hardware capital investments spanning compute, accelerator, storage, networking, and orchestration layers, while driving platform adoption, utilization, and business value realization through measurable product outcomes
• Serve as the key decision-maker for product prioritization and strategic direction across the AI Infrastructure product area, balancing competing demands, investment tradeoffs, delivery sequencing, and alignment with senior stakeholders
• Analyze market trends and competitive signals to inform investment decisions, capital allocation, and vendor strategy across hyperscale providers, Neo Clouds, edge platforms, and serverless GPU providers
• Identify and prioritize target market segments, qualify demand signals, and align product capabilities to address unmet customer needs across lines of business
• Lead and develop Product Managers and Senior Product Associates while driving cross-functional collaboration and harnessing AI to improve efficiency, scalability, rapid prototyping, and responsiveness across a complex, matrixed environment

• 8+ years of experience or equivalent expertise delivering products, projects, or technology applications
• Extensive knowledge of the product development life cycle, technical design, and data analytics
• Proven ability to influence the adoption of key product life cycle activities including discovery, ideation, strategic development, requirements definition, and value management
• Experience driving change within organizations and managing stakeholders across multiple functions
• Extensive experience in high-performance compute, GPU-accelerated, data center, or AI infrastructure
• Deep knowledge of the AI infrastructure stack across compute, accelerators, high-speed interconnects, networking, storage, and orchestration layers, with experience across technologies such as Nvidia GPUs, Infini Band, Spectrum-X, Arista, DDN, VAST Data, and Kubernetes
• Understanding of AI Factory reference architectures and how infrastructure decisions impact performance, cost, scalability, and…