
Job Overview
Location
Singapore
Job Type
Full-time
Category
Software Engineering
Date Posted
April 27, 2026
Full Job Description
đź“‹ Description
- • The Solution Architect at FuriosaAI Inc. will serve as a critical technical and strategic contributor, responsible for designing and supporting enterprise and cloud-based AI solutions using advanced Tensor Contraction Processor technologies, while driving customer adoption and engagement across the APAC region.
- • Day-to-day responsibilities include developing end-to-end technical architectures, providing hands-on guidance on integrating AI accelerators and server LLMs into customer environments, leading pre-sales activities such as technical presentations and proof-of-concepts, collaborating with engineering and product teams to influence roadmap decisions, and mentoring a team of solution architects to foster technical excellence and collaboration.
- • FuriosaAI Inc. is an innovative AI hardware company focused on advancing AI acceleration through its Tensor Contraction Processor technology, operating in a dynamic, collaborative culture that values continuous learning, creative problem-solving, and shaping the future of enterprise and cloud AI solutions.
- • In this role, the Solution Architect will deepen expertise in AI hardware ecosystems, gain strategic influence over product direction based on real-world customer feedback, develop leadership and cross-functional collaboration skills, and establish themselves as a trusted advisor and industry thought leader in advanced AI acceleration technologies.
Skills & Technologies
About FuriosaAI Inc.
FuriosaAI is a South-Korean semiconductor startup that designs high-performance AI inference processors and accelerator cards. Founded in 2017 by former Samsung and AMD engineers, the company develops energy-efficient chips such as the Warboy and Renegade series, optimized for data-center and edge workloads. Its hardware supports common ML frameworks and targets computer-vision and large-language-model applications, aiming to reduce power consumption and total cost of ownership for cloud and enterprise customers.
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