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Sales Engineer

Aisquared

Mountain View, CA, USonsiteOther

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About this role

About the Role:

We are looking for a highly motivated Sales Engineer with a strong background in AI infrastructure to join our dynamic team. In this role, you will play a critical part in driving enterprise sales, supporting both pre-sales and post-sales activities, and partnering closely with account executives to deliver cutting-edge solutions to our clients.

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 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.

Qualifications:

• 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.

• Familiarity with machine learning workflows , MLOps tools, and data engineering best practices.

• A proactive mindset and a customer-first attitude.

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