Pear VC

Pear VC

Technical Customer Success Engineer - Spur

New York City

Sponsorship not specifiedDetected 115 days ago
CI/CDLLMsAgentic AIFigmaCustomer SuccessTest AutomationAPI TestingCommunication

About the role

  • We're looking for a Technical Customer Success Engineer to help our customers succeed with AI-driven testing in real production environments.
  • You'll start by shadowing experienced Solution Engineers, working closely with our Account Executives, and gradually take ownership of customers, pilots, and test strategies.

Responsibilities

  • Author, maintain, and improve AI-powered test flows for customer applications
  • Monitor and track customer activity, engagement and relay product feedback to design and engineering teams
  • Partner with Account Executives during onboarding, demos, and spurring sessions
  • Feed real-world learnings back into product and engineering to drive platform improvement
  • Gradually take full ownership of customer accounts and lead technical conversations

Requirements

  • 3-4 years experience in Customer Success Roles
  • Comfort with Technical Concepts
  • Strong understanding of web applications and browser behavior

Nice to have

  • Automation experience with any framework
  • QA / Testing Experience
  • Basic scripting knowledge or eagerness to learn
  • Exposure to CI/CD or API testing
  • Interest in AI, LLMs, or prompt engineering
  • In-person role based in our NYC office
  • Spur is an Equal Opportunity Employer committed to diversity and inclusion in the workplace.

Benefits

  • Equity package
  • Benefits offering (Gym & Wellness Stipends, Meal Stipends, OffSites)
  • Support pilots and production usage by improving test reliability and coverage

Company info

  • We want to help our customers deliver the best digital experiences
  • Read our Manifesto: https://www.spurtest.com/founders-letterhttps://www.spurtest.com/manifesto
  • Work directly with customers to help them adopt and succeed with Spur's AI-driven testing platform

This listing is sourced directly from Pear VC's careers page and normalized into a canonical job model.