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Roles and responsibilities

As a Sales Engineer, you will serve as a vital bridge between cutting-edge technology and business requirements, primarily focusing on our GPU-as-a-Service (GPUaaS) platform. Collaborating closely with the Enterprise AI Sales team, you will identify and qualify leads that require significant AI workloads, ensuring a strong understanding of client needs.

Your responsibilities will include delivering technical presentations, conducting product demonstrations, and developing proof-of-concept (POC) projects to illustrate the advantages of our GPUaaS solutions. You will translate customer requirements into detailed technical specifications for GPU configurations and compute resources, enabling tailored solutions that align with client objectives.

In partnership with the sales team, you will create compelling proposals that highlight the cost-effectiveness and scalability of our offerings compared to traditional methods. You’ll also collaborate with pre-sales engineers to set up and implement POC environments, showcasing the platform's performance and efficiency.

Throughout the sales cycle, you will provide ongoing technical support, addressing customer inquiries and concerns to facilitate a smooth process. Staying current with advancements in AI, GPU technology, and our platform's features will be crucial for maintaining a competitive edge and delivering the best solutions to our clients. Your role will be integral to driving successful AI solution deployments and fostering strong client relationships.

Desired candidate profile

Requirements:

• Minimum 3+ years of experience in a technical sales role, preferably within the AI or high-performance computing (HPC) space
• Strong understanding of GPU architectures, their capabilities, and their role in accelerating AI workloads, specifically GPUs like A100s and H100s
• Familiarity with AI frameworks and libraries (e.g., TensorFlow, PyTorch) is a plus
• Excellent communication and presentation skills with the ability to explain complex technical concepts to a non-technical audience
• Ability to work effectively in a collaborative environment and build strong relationships with both internal and external stakeholders
• Proficient in technical documentation and adept at creating clear and concise proposals; speaking Mandarin is a big bonus
• Experience working with AI enterprises and understanding their specific needs
• Knowledge of containerization technologies like Docker or Kubernetes
• Experience developing or managing POC environments for AI projects, specifically deploying GPU clusters