Enterprise Data & AI Deployment Architect

ThoughtSpot; Mountain View, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

In-office 3+ days/week

Job summary

ThoughtSpot seeks an experienced, hands-on Solutions Architect to own and architect deployments for our most strategic customers. You will design production-grade data models, embedding patterns, and governance structures that scale with real usage and security reviews.

You'll drive deployments from kickoff to production, remove blockers, and turn complex implementations into reusable patterns. You will voice customer needs to Product and collaborate with Sales Engineering, Product, and Customer

Qualifications

• Hands-on, architect-level technical delivery and deployment
• Understanding of enterprise data modeling, governance, and security
• Ability to communicate early and clearly with customers and internal teams

Responsibilities

• Own the technical relationship with strategic customers and design scalable ThoughtSpot Analytics deployments
• Build production-ready data models, embedding patterns, and governance structures for real usage
• Lead deployments from kickoff to production and unblock blockers to go-live
• Create reusable architecture patterns to accelerate future deployments
• Advocate for customer needs in Product and feedback loops
• Document best practices to reduce tribal knowledge and improve scalability

Skills

Hands-on architect

Customer relationship

Enterprise data modeling

Governance & security

Clear communication

Strategic deployment

Ownership & accountability

Job description

ThoughtSpot seeks an experienced, hands-on Solutions Architect to own and architect deployments for our most strategic customers. You will design production-grade data models, embedding patterns, and governance structures that scale with real usage and security reviews.

You'll drive deployments from kickoff to production, remove blockers, and turn complex implementations into reusable patterns. You will voice customer needs to Product and collaborate with Sales Engineering, Product, and Customer