Aisquared5mo ago

Sales Engineer

United States·Mountain Viewmid

SalesSales Engineer

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Quick Summary

Overview

About the Role: We are looking for a highly motivated Sales Engineer with a strong background in AI infrastructure to join our dynamic team.

Key Responsibilities

Leverage 10+ years of experience as a Sales Engineer to drive technical sales processes and customer success. Sell AI-related infrastructure solutions to large and mid-sized enterprises , identifying client needs and aligning our solutions with…

Requirements Summary

Proven experience in technical sales, ideally focused on AI, cloud, or data infrastructure. Strong communication and presentation skills with the ability to influence both technical and business stakeholders.

Technical Tools

SalesSales Engineer

About the Role

~1 min read

Responsibilities

~1 min read

→Leverage 10+ years of experience as a Sales Engineer to drive technical sales processes and customer success.

→Sell AI-related infrastructure solutions to large and mid-sized enterprises, identifying client needs and aligning our solutions with their strategic goals.

→Partner with Account Executives to enable account-based marketing and selling (ABM/ABS) strategies.

→Operate as a self-starter, capable of working autonomously with minimal supervision in a fast-paced environment.

→Support pre-sales activities including product demonstrations, proof-of-concepts, RFP responses, and technical deep dives.

→Assist with post-sales enablement to ensure successful deployment and customer satisfaction.

→Provide deep technical knowledge of cloud-native technologies, tools, and architecture best practices.

→Demonstrate a strong understanding of AI and data pipelines, enabling clients to build scalable, intelligent solutions.

Requirements

~1 min read

Proven experience in technical sales, ideally focused on AI, cloud, or data infrastructure.

Strong communication and presentation skills with the ability to influence both technical and business stakeholders.

Deep knowledge of cloud platforms (AWS, GCP, Azure), cloud-native ecosystems (Kubernetes, containers, CI/CD, etc.), and cloud-native AI tools and infrastructure—such as Amazon SageMaker, Google Vertex AI, Azure Machine Learning, Kubeflow, MLflow, and data pipeline orchestration tools like Apache Airflow and Argo Workflows.