Solution Manager - Global Tech (AI Hardware/ HPC/ Semiconductor | 5-8m Bonus)

About the role

Own the full lifecycle product strategy and execution for the AI compute portfolio—GPUs, servers, and networking—so it fits with the overall AI and hybrid cloud direction. Build deep expertise across AI hardware (including GPU/accelerator platforms), AI software stack, and hybrid cloud / cloud-native deployment approaches; act as a liaison between engineering delivery teams and sales stakeholders.

Key responsibilities

• Own the full lifecycle product strategy and execution for the AI compute portfolio—GPUs, servers, and networking—so it fits with the overall AI and hybrid cloud direction
• Set priorities for features, technical capabilities, and investment themes using market signals, competitor offerings, and ongoing customer input
• Build deep expertise across AI hardware (including GPU/accelerator platforms), AI software stack, and hybrid cloud / cloud-native deployment approaches; act as a liaison between engineering delivery teams and sales stakeholders
• Back pre-sales engagements, including RFI/RFP responses, executive-level presentations, and hands-on customer workshops
• Function as the technical authority on AI compute and reference deployment architectures for the assigned customer accounts
• Convert customer business and technical requirements into actionable product inputs—clear requirements, an aligned user roadmap, and delivery timelines

About You

• Bachelor's degree or higher in Telecommunications, Information Systems Management, Electrical Engineering, or a closely related field
• At least 5 years of experience in pre-sales, product management, or solution consulting for AI-focused products/services—preferably within AI infrastructure, HPC, or semiconductor domains
• Experience in closing opportunities and building long-term relationships with enterprise customers, such as local enterprises and MNCs, Government bodies, FSI, or Telecom organizations
• Familiarity with the design and software/ecosystem of AI processors and servers (e.g., AI Cloud, ARM architecture) is advantageous