F

Fal

NLP-based sentiment & anomaly detection

Enterprise Account Executive Manager

Account ExecutiveUpdated on Nov 13
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • At least 8 years of B2B sales experience, including at least 3 years leading quota-carrying Enterprise teams.
  • A track record of hitting team targets, with measurable results that can be discussed.
  • Experience selling technical products such as application programming interfaces, cloud, data, developer platforms, or artificial intelligence/machine learning.
  • Experience selling consumption- or usage-based products, including committed-spend contracts and expansion from usage.
  • Experience working in fast-paced, ambiguous environments and owning outcomes end to end.
  • Ability to run C-level meetings and pricing negotiations.

Responsibilities

  • Own the North America, Middle East, and Africa Enterprise number, including team quota, forecast accuracy, and pipeline coverage.
  • Hire, onboard, and develop a team of Enterprise Account Executives, setting and maintaining a high performance bar.
  • Participate directly in the largest deals through executive sponsorship, pricing, negotiation, and closing.
  • Build the operating rhythm through deal reviews, forecast calls, pipeline inspection, and win/loss analysis.
  • Shape sales of usage-based infrastructure, including deal desk processes, commit structures, and expansion motions.
  • Work with Solutions Engineering, Product, and Marketing to relay field feedback to the roadmap.
  • Create the sales playbook.

Desired Qualifications

  • Experience as Head of Sales or as the first sales leader at a Series A–B company, building the team from scratch.
  • Relationships with buyers in media, entertainment, e-commerce, gaming, advertising, or consumer apps.
  • Curiosity about generative media and experience experimenting with its models.

About the Company

Fal

NLP-based sentiment & anomaly detection

Fal.ai enables data-driven businesses to improve analytics using natural language processing and machine learning, focusing on sentiment analysis and anomaly detection within dbt data models. It analyzes text such as customer reviews, support tickets, and surveys to classify sentiment (positive, negative, neutral) and spots unusual patterns in data transformations. The service integrates with existing data infrastructure that uses dbt models and is sold through tiered subscriptions that include basic sentiment analysis, advanced anomaly detection, and premium support. Its goal is to help organizations make informed decisions and improve customer satisfaction by delivering continuous analytics enablement and actionable insights.

Company size
201-500
Company stage
Late Stage VC
Total funding
$2.2B
Headquarters
Seattle, WA
Founded
2021

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