Enterprise AI/ML Infra Sales Executive – East

Space Executive

Berkeley (CA)

On-site

USD 180,000 - 280,000

Full time

14 days+
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Job summary

Space Executive is seeking an Enterprise Account Executive on the East Coast to own the full sales cycle from prospecting to close with Fortune 1000 and high-growth enterprises. You will sell an advanced AI/ML observability and evaluation platform to enterprise data science and ML teams.

Ideal candidates have 5+ years in Enterprise SaaS sales, a proven quota attainment record, and the ability to engage ML, data, and engineering stakeholders.

Qualifications

  • 5+ years of Enterprise SaaS sales experience, especially in tech/infrastructure products.
  • Proven track record of meeting or exceeding quotas in complex, multi-stakeholder cycles.
  • Experience selling to ML, Data, Engineering, or AI/innovation groups is a strong plus.

Responsibilities

  • Own and drive complex enterprise sales cycles from first touch to close.
  • Build and manage a healthy pipeline across Fortune 1000 and high-growth accounts.
  • Develop deep understanding of customers’ ML workflows, pain points, and evaluation needs.
  • Partner closely with Sales Engineering to deliver high-impact demos and technical presentations.
  • Provide customer-driven insights to product leadership to influence roadmap and GTM strategy.
  • Represent the company at industry events and virtual sessions.
  • Consistently meet and exceed quarterly and annual revenue targets.

Skills

Enterprise SaaS sales
Strategic selling
Technical acumen
Stakeholder management

Tools

SFDC (Salesforce)
Video conferencing

Job description

Space Executive is seeking an Enterprise Account Executive on the East Coast to own the full sales cycle from prospecting to close with Fortune 1000 and high-growth enterprises. You will sell an advanced AI/ML observability and evaluation platform to enterprise data science and ML teams.

Ideal candidates have 5+ years in Enterprise SaaS sales, a proven quota attainment record, and the ability to engage ML, data, and engineering stakeholders.

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