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Arize AI

AI model observability and evaluation platform

AI Sales Engineer

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedRemote

About the Job

Requirements

  • Have 3+ years of experience in a customer-facing role such as sales engineer, solutions engineer, or forward deployed engineer.
  • Be able to simplify complex technical concepts.
  • Be proficient in Python and TypeScript.
  • Know LLM and agentic frameworks such as OpenAI Agents SDK, Google ADK, LangGraph, and DSPy.
  • Understand generative AI concepts and the application evaluation and development lifecycle.

Responsibilities

  • Partner with account executives to articulate the Arize value proposition, vision, and strategy to customers.
  • Work closely with sophisticated generative AI teams.
  • Act as a trusted advisor to prospective customers and build relationships with technical and business stakeholders.
  • Lead product demonstrations of the Arize platform.
  • Advise on generative AI and machine learning best practices.
  • Lead discovery to understand prospects’ generative AI technology stacks and collaborate with the Sales team to construct a compelling value proposition for the Arize platform.
  • Lead proof-of-concept motions with prospective buyers.
  • Handle technical objections and develop strategies across Sales, Engineering, and Product to resolve them.

Desired Qualifications

  • Have previous experience working across and aligning Sales, Product, and Engineering.
  • Have previous experience within a team that underwent a high-growth stage.
  • Have previous engineering experience in Data Engineering, MLOps, Kubernetes, or GCP, AWS, or Azure.

About the Company

Arize AI

AI model observability and evaluation platform

Arize AI provides a platform for AI observability and LLM evaluation that helps top AI teams monitor and improve models across NLP, computer vision, and recommender systems. It works by offering analytics, LLM traces, spans, RAG analysis, and task-based evaluations to troubleshoot issues and measure performance. It differentiates itself by delivering end-to-end observability and evaluation in a single platform with embedding visualization for RAG to pinpoint missing or irrelevant context. Its goal is to help AI teams ensure their models perform optimally and continuously improve their AI systems.

Company size
201-500
Company stage
Acquired
Total funding
$131M
Headquarters
Berkeley, CA
Founded
2020

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