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AI Sqaured

Integrates AI models into business apps

Sales Engineer

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeMountain View, CA, USANo salary listedIn-person

About the Job

Requirements

  • 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.

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.

About the Company

AI Sqaured

Integrates AI models into business apps

Squared.ai builds AI-powered solutions for businesses by integrating predictive and generative AI into business applications. It prepares foundational models and large language models and connects them in real time to mission-critical apps, with intuitive UX so end users can access AI insights without long development cycles. It differentiates itself by focusing on end-to-end deployment, real-time performance monitoring, auto-tuning, and feedback loops to maintain accuracy and adoption across teams, bridging data science with business units. Its goal is to democratize AI-driven decision-making by delivering deployable AI capabilities that boost adoption and enable faster AI-powered decision making in existing workflows.

Company size
51-200
Company stage
Series A
Total funding
$19.8M
Headquarters
Washington DC, District of Columbia
Founded
2021

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