Forward Deployed Engineer at AI Squared

A
AI Squared

Forward Deployed Engineer

us flag
United States

Hybrid

Full Time

#AI

#Cloud Infrastructure

#Sales

#Technical Sales

#Cloud Platforms

#Machine Learning

#MLOps

#Data Pipelines

#Kubernetes

#CI CD

#Customer Success

#Presentation Skills

AI Squared is looking for a Forward Deployed Engineer

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About the Role: 


 We are looking for a highly motivated Forward Deployed 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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