Enterprise Customer Success Manager

Overview

The Role:

The Enterprise CSM is a unique blend of a technical expert and strategic relationship builder. You will drive adoption within a portfolio of Fortune 5000 accounts, moving beyond traditional BI to help customers deploy AI Agents and Embedded Analytics. You’ll be as comfortable discussing API authentication with a developer as you are discussing ROI with a CDO.

• Account Strategy:
  Be part of a focused team managing multiple Fortune 5000 accounts, responsible for driving adoption, tying usage to business problems, and building expansion opportunities through passive selling.
• Champion Agentic AI:
  Partner with customers to move from dashboards to agents, helping them leverage Thought Spot Agents and LLM-based workflows to automate data insights.
• 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/Big Query) is optimized for AI-driven search.
• Voice of the Customer:
  Act as the primary technical point of contact, communicating requirements and use cases in a way that is actionable for Thought Spot’s Product, Engineering, and Marketing teams.
• Relationship Management:
  Foster robust relationships through proactive champion building, acting as the bridge between human business needs and complex data technicalities.
• Bridge Business and Technology:
  Translate customer business goals into technical requirements and, conversely, explain the business value of technical features to stakeholders.
• Technical Enablement:
  Run advanced workshops and live demos that showcase the "Art of the Possible" with AI, embedding, and agentic analytics.

• A Consultative Problem Solver:
  You have a knack for understanding complex business challenges and prescribing elegant technical solutions.
• Technically Curious:
  You have a deep passion for the data space and are constantly learning about new technologies like LLMs and Generative AI.
• Incredible Communicator:
  You can command a room of data architects and then pivot to explain a technical concept in simple terms to a business leader.
• Proactive & Eager to Help:
  You are a natural problem solver who enjoys diving in to help customers with their initial technical hurdles.
• Language
  
  Skills:
  
  Fluent in English and capable of speaking European languages (e.g., French, Spanish, German) in a business environment.

• 5+ years in a customer-facing technical role (Technical CSM, Solutions Architect, or Sales Engineer) within the Data/SaaS space.
• Analytics & AI Depth:
  Strong knowledge of the modern data stack (Snowflake/Big Query/Databricks) and an understanding of LLM-based applications or AI Agents.
• Developer Literacy:
  Proficiency in SQL and familiarity with JavaScript/Type Script frameworks (React, Angular, or Vue) for supporting embedded use cases.
• Integration Knowledge:
  Comfort discussing REST APIs, webhooks, and security protocols like SAML/OIDC.
• The "Consultative Edge":
  Ability to translate complex technical "how-to" into strategic "why-it-matters" for executive stakeholders.
• Education:
  
  Master’s/Bachelor’s Degree preferred but not required.

#LI-Hybrid

#LI-JV2

Spotters are expected to demonstrate AI literacy and workflow integration, including the ability to:

• Comfortably and confidently integrate artificial intelligence into daily workflows to increase productivity and quality.
• Hands-on experience leveraging AI tools (industry-leading LLMs) to increase productivity, automate routine tasks, and improve work quality.
• Describe experience using AI for research, content creation, and document summarization while maintaining ownership of judgment and final decisions.
• Write effective prompts to obtain accurate and creative results from AI tools.

Spotters are expected to exemplify these key traits and AI Mindset:

• Curiosity in exploring new AI tools
• Adaptability to quickly learn and implement new, emerging AI technologies
• Critical thinking to know when to identify when AI should be used versus when human judgement is necessary

This combination of curiosity, adaptability,…