AI Sales Engineer

Position Overview

AI is rapidly transforming the world, and Arize AI is at the forefront as the leading AI observability and evaluation platform. We empower AI engineers to build and deploy high-performing, reliable models, ensuring teams have the tools to monitor, troubleshoot, and improve AI in production, especially as the landscape shifts towards generative AI and agentic systems.

The Team

Our engineering team builds systems that interact with some of the most complex software ever deployed in production. Composed of industry veterans with experience in deep learning infrastructure, autonomous drones, ridesharing marketplaces, and ad tech, we are seeking an AI Sales Engineer to join our mission to get our product into the hands of every Machine Learning organization.

Responsibilities

As an AI Sales Engineer, you will:

Trusted Advisor to the Customer:

• Build relationships with technical stakeholders.
• Lead product demonstrations of the Arize platform.
• Lead discovery to understand prospect’s ML stack and collaborate with the Sales team to construct a compelling value proposition for the Arize Platform.
• Handle technical objections and develop strategies across sales, engineering, and product to overcome them.

Domain Expert within AI/ML:

• Write educational and compelling blog posts about ML and MLOps related topics.
• Collaborate to create and enhance documentation, recorded video assets, and other publically available as well as internal enablement materials.
• Engage in relevant ML communities online to raise awareness on challenges of deploying ML in production.

Requirements

Strong Communication Skills:

• Ability to empathize with the frame of reference of those you are communicating with and tailor your message and approach accordingly.
• Ability to simplify complex, technical concepts.

Quick and Self-Learner:

• Undeterred by the technical complexity of production ML deployments; welcome the challenge to learn and develop your own point of view.
• Ask the right questions with the customer to uncover nuances in their unique deployments.
• Ability to work within ambiguity and take action with limited direction.

Knowledgeable in Machine Learning:

• Understand the difference between Linear Regression and Boosted Trees and the advantages/disadvantages of each.
• Experience training models in common packages such as scikit-learn, HuggingFace, fastai, etc.

5+ Years in Customer-Facing Role:

• Experience in pre-sales, technical account management, or consulting.
• Experience working with customers within the high enterprise (e.g., Fortune 500, etc.).

Proficiency in:

• Python
• Linux/Unix

Bonus Points, But Not Required

• Previous experience working across and aligning Sales, Product, and Engineering.
• Previous experience within a team that underwent a high growth stage.
• Previous engineering experience in: Data Engineering, MLOps, Kubernetes, GCP / AWS / Azure.

Compensation

• Salary: The estimated annual salary and variable compensation for this role is between $140,000 - $200,000.
• Equity: A competitive equity package is included.
• Note: Actual compensation is determined based upon a variety of job-related factors, including transferable work experience, skill sets, and qualifications. Total compensation also includes...

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