Enterprise Customer Success Manager

ThoughtSpot ThoughtSpot · Data AI · London, United Kingdom

Enterprise Customer Success Manager role focused on driving adoption of AI Agents and Embedded Analytics within Fortune 5000 accounts. The role involves strategic account management, technical guidance on API/SDK usage, and acting as a liaison between customers and internal product/engineering teams. Requires strong knowledge of modern data stacks and LLM-based applications.

What you'd actually do

  1. Account Strategy: Be part of a focused team managing multiple Fortune 5000 accounts, responsible for driving adoption, tie usage to business problems, and build expansion opportunities through passive selling.
  2. Champion Agentic AI: Partner with customers to move from "dashboards" to "agents," helping them leverage ThoughtSpot Agents and LLM-based workflows to automate data insights.
  3. Architect & Advise: Guide technical stakeholders through the development lifecycle of building high-performance data apps using our APIs and SDKs, while ensuring their data stack (Snowflake/Databricks/BigQuery) is optimized for AI-driven search.
  4. Voice of the Customer: Act as the primary technical point of contact, communicating requirements and use cases in a way that is actionable for ThoughtSpot’s Product, Engineering, and Marketing teams.
  5. Relationship Management: Foster robust relationships through proactive champion building, acting as the bridge between human business needs and complex data technicalities.

Skills

Required

  • Customer Success
  • Technical Account Management
  • Solutions Architecture
  • Sales Engineering
  • Data/SaaS space
  • Modern data stack (Snowflake/BigQuery/Databricks)
  • LLM-based applications
  • AI Agents
  • SQL
  • JavaScript/TypeScript frameworks (React, Angular, or Vue)
  • REST APIs
  • webhooks
  • SAML/OIDC

Nice to have

  • European languages (French, Spanish, German)

What the JD emphasized

  • 5 years in a customer-facing technical role
  • Strong knowledge of the modern data stack
  • understanding of LLM-based applications or AI Agents