Full-Time

Enterprise Account Executive

Confirmed live in the last 24 hours

Arize AI

Arize AI

51-200 employees

AI observability and model evaluation platform

Data & Analytics
AI & Machine Learning

Compensation Overview

$250k - $300kAnnually

+ Equity Package

Senior

Remote in USA

Remote-first company with offices in New York City and San Francisco Bay Area; WFH monthly stipend for co-working spaces.

Category
Field Sales
Sales & Account Management
Required Skills
Machine Learning

You match the following Arize AI's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • 5+ years enterprise SaaS sales experience: Hungry, aggressive and motivated
  • Familiarity or willingness to learn sales technologies to find and attract prospects
  • Self-starter and comfortable working in limited process environments
  • Full-cycle sales experience and ability to navigate the complexities of enterprise deals
  • Fast-paced and focused on helping prospects / customers
  • Team player: Collaboration with peers and other organizations within Arize is critical to success, we deeply value the success of the collective team over individual gains
  • Strong communication skills: Clearly and objectively communicate observations from the field
Responsibilities
  • Be a networker, seller and closer
  • Build relationships with AI/ML stakeholders and be an active member of the community
  • Conduct discovery with prospects and share the Arize vision
  • Run a sophisticated prospecting strategy to 'get the word out' and find deals
  • Create sales plays, write talk tracks and strategically identify new business opportunities
  • Deeply research accounts, stakeholders and competitors
  • Manage proof of concepts, drive adoption and grow accounts
  • Manage and navigate internal / external stakeholders to ensure success
  • Understand use cases, scope licensing and find more workloads
  • BANT or MEDDIC methodology preferred
Desired Qualifications
  • Previous selling experience in Software Engineering
  • Previous selling experience in Data Science
  • Previous selling experience in Machine Learning

Arize AI provides a platform focused on AI observability and evaluating language models. The platform allows companies to monitor and troubleshoot their machine learning models, including those used for natural language processing, computer vision, and recommendations. Users can access analytics and workflows to identify and fix issues in their AI systems, ensuring optimal performance. Key features include task-based evaluations for aspects like hallucination and relevance, as well as tools for visualizing query and knowledge base embeddings to enhance retrieval accuracy. Unlike competitors, Arize emphasizes a comprehensive approach to model evaluation and troubleshooting, catering specifically to the needs of leading AI companies. The goal of Arize AI is to help these companies continuously improve their AI models and maintain high performance.

Company Size

51-200

Company Stage

Series B

Total Funding

$59.3M

Headquarters

Berkeley, California

Founded

2020

Simplify Jobs

Simplify's Take

What believers are saying

  • Increased demand for AI observability tools boosts Arize AI's market potential.
  • Collaboration with Microsoft enhances Arize AI's enterprise deployment capabilities.
  • Prompt variable monitoring highlights Arize AI's commitment to LLM performance enhancement.

What critics are saying

  • Competition from tech giants like Microsoft may overshadow Arize's offerings.
  • Rapid tech advancements could render Arize's features obsolete if not updated.
  • Data privacy compliance in the EU poses challenges for Arize AI.

What makes Arize AI unique

  • Arize AI offers industry-first AI Copilot for troubleshooting AI systems.
  • The platform provides unique prompt engineering and retrieval tracing workflows.
  • Arize AI supports EU data residency, addressing regional data privacy concerns.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Retirement Plan

Unlimited Paid Time Off

Parental Leave

Mental Health Support

Flexible Work Hours

Growth & Insights and Company News

Headcount

6 month growth

1%

1 year growth

1%

2 year growth

1%
Arize AI
Nov 21st, 2024
Arize AI Is Named An Emerging Leader In the Generative AI Engineering Gartner(R) Emerging Market Quadrant

Arize AI is named an Emerging Leader in the Generative AI engineering gartner(r) Emerging Market quadrant.

PR Newswire
Nov 20th, 2024
Arize Ai Collaborates With Microsoft To Enable More Effective Enterprise Deployment Of Generative Ai

Arize AI now offers an integrated development experience on Microsoft Azure AI Foundry portal, SDK, and Command Line Interface (CLI). CHICAGO, Nov. 19, 2024 /PRNewswire/ -- Arize AI, a leader in AI observability and LLM evaluation, debuted a deeper collaboration with Microsoft and a raft of new integrations at Microsoft Ignite today. The updates come at a critical inflection point for enterprise adoption of generative AI. Despite the fact that most enterprises are planning production deployments of LLMs, over half still cite issues like data privacy and difficulty pinpointing issues (i.e. accuracy of responses) as barriers standing in the way of moving from prototype to successful real-world deployment

Arize AI
Sep 19th, 2024
Arize Release Notes: AI Search V2, Copilot Updates, and More

Arize AI, Inc is excited to announce the release of AI Search V2, packed with new features and improvements designed to enhance the user experience.

PR Newswire
Jul 11th, 2024
Arize Ai Introduces Ai Copilot

Industry-first AI assistant for troubleshooting AI and other new updates promise to speed development for AI engineersSAN FRANCISCO, July 11, 2024 /PRNewswire/ -- Arize AI, a pioneer and leader in AI observability and LLM evaluation, today debuted new capabilities to help AI developers evaluate and debug LLM systems. The premiere is one among many taking place at the Arize:Observe conference today, where speakers – including OpenAI, Lowe's, Mistral, Microsoft, NATO, and others – are sharing the latest research, engineering best practices, and open source frameworks.Arize Copilot – the industry's first AI assistant to troubleshoot AI systems – is a new tool that surfaces relevant information and suggests actions in the Arize platform, automating complex tasks and taking actions to help AI engineers save time and improve app performance. Examples where the AI Copilot can help out of the box include getting model insights, prompt optimization, building a custom evaluation, and AI search."Using AI to troubleshoot complex AI systems is a logical next step in the evolution of building generative AI applications, and we are proud to offer Arize Copilot to teams that want to improve the development and performance of LLM systems," said Aparna Dhinakaran, Chief Product Officer and Co-Founder of Arize.Other new workflows debuting today in the Arize platform promise to help engineers find issues with LLM apps once they are deployed. With AI search, for example, teams can select an example span and easily discover all similar issues (i.e. finding all data points where a customer is frustrated). Teams can then save those data points into a curated dataset to apply annotations, run evaluation experiments, or kick off fine-tuning workflows.Altogether, the updates make Arize a powerhouse for experimentation as well as production observability

PR Newswire
Aug 30th, 2023
Arize Ai Unveils Prompt Engineering And Retrieval Tracing Workflows For Llm Troubleshooting

SAN FRANCISCO, Aug. 30, 2023 /PRNewswire/ -- Arize AI, a market leader in machine learning observability, debuted industry-first capabilities for troubleshooting large language models (LLMs) at Google Cloud Next '23 today.Arize's new prompt engineering workflows, including a new prompt playground, enables teams to find prompt templates that need to be improved, iterate on them in real time, and verify improved LLM outputs.Prompt analysis is an important component in troubleshooting an LLM's performance. Often, LLM performance can be improved simply by testing different prompt templates, or iterating on one to achieve better responses.With these new workflows, teams can:Uncover responses with poor user feedback or evaluation scoresIdentify the template associated with poor responsesIterate on the existing prompt templateCompare responses across prompt templates in a prompt playgroundArize is also launching additional search and retrieval workflows to help teams using retrieval augmented generation (RAG) troubleshoot where and how the retrieval needs to be improved. These new workflows will help teams identify where they may need to add additional context into their knowledge base (or vector database), when the retrieval didn't retrieve the most relevant information, and ultimately understand why their LLM may have hallucinated or generated sub-optimal responses."Building LLM-powered systems that responsibly work in the real-world is still too difficult today," said Aparna Dhinakaran, Co-Founder and Chief Product Officer of Arize. "These industry-first prompt engineering and RAG workflows will help teams get to value and resolve issues faster, ultimately improving outcomes and proving the value of generative AI and foundation models across industries."About Arize AIArize AI is a machine learning observability platform that helps ML teams deliver and maintain more successful AI in production. Arize's automated model monitoring and observability platform allows ML teams to quickly detect issues when they emerge, troubleshoot why they happened, and improve overall model performance across both structured data and image and large language models

VentureBeat
Aug 30th, 2023
Arize Ai Wants To Improve Enterprise Llms With ‘Prompt Playground,’ New Data Analysis Tools

Head over to our on-demand library to view sessions from VB Transform 2023. Register Here. We all know enterprises are racing at varying speeds to analyze and reap the benefits of generative AI — ideally in a smart, secure and cost-effective way. Survey after survey over the last year has shown this. But once an organization identifies a large language model (LLM) or several it wishes to use, the hard work is far from over. In fact, deploying the LLM in a way that benefits an organization requires understanding the best prompts employees or customers can use to generate helpful results — otherwise it’s pretty much worthless — as well as what data to include in those prompts from the organization or user.“You can’t just take a Twitter demo [of an LLM] and put it into the real world,” said Aparna Dhinakaran, cofounder and chief product officer of Arize AI, in an exclusive video interview with VentureBeat

Arize AI
Aug 1st, 2024
Arize AI: Support for EU Data Residency

Arize AI recently rolled out EU data residency for all users, enabling customers to host their data within the European Union.

Inside Lighting
Nov 27th, 2023
Acuity Brands to Acquire Horticultural Brand From Current

Acuity Brands' rival, Signify, acquired Austin, Texas-based Fluence in 2022 for $272 million.

Hacker Noon
Apr 14th, 2024
Arize AI Leads the Way in AI Observability with Prompt Variable Monitoring

Arize AI, an AI observability and large language model (LLM) evaluation platform, launched prompt variable monitoring and analysis onstage at Google Cloud Next '24 this week.

VentureBeat
Jul 17th, 2023
Vb Transform Innovation Showcase Winner: Arize Ai

Head over to our on-demand library to view sessions from VB Transform 2023. Register Here. There are many companies innovating in the generative AI, machine learning (ML) and analytics spaces. Ten were nominated at the Innovation Showcase at this year’s VentureBeat Transform. Ultimately, three winners were selected in three categories: Best Presentation Style, Best Technology and Most Likely to Succeed. For Best Technology, judges chose Arize AI, an ML observability platform that uses AI to troubleshoot AI. Cofounder and CEO Jason Lopatecki described the company’s Observe Copilot as an observability assistant for AI and ML scientists that allows them to monitor, troubleshoot and fine-tune large language models (LLMs) and generative, recommender, machine learning (ML), computer vision and natural language processing (NLP) models. Follow all our VentureBeat Transform 2023 coverageLopatecki explained that the typical data troubleshooting process has been manual and tedious