RVP, AI Outcomes Architecture

Thought Spot is a Data & AI platform that helps companies turn data into enterprise advantage. We're Gartner MQ leaders with more than 1,000 customers globally and offices in Mountain View, Chicago, London, Bangalore, Sydney, and Tokyo.

The RVP, AI Outcomes Architecture builds and leads the technical and delivery engine of Customer Outcomes. You lead three organizations – the AI Outcomes Architects, who own the technical architecture; the AI Outcomes Analysts, who own the hands-on build; and the AI Deployment Managers, who own delivery and the timeline – so that every Liveboard, Spotter agent, and Data App we ship is production-grade and the value promised during the sale is actually achieved.

You report directly to the VP of Customer Outcomes and work closely with the AI Outcomes Manager organization, which owns the customer relationship, and with Thought Spot's Product and Engineering leadership – you are the executive backstop for every deployment.

• Build and lead a global organization. Hire, develop, and manage the AI Outcomes Architect, AI Outcomes Analyst, and AI Deployment Manager teams across North America, EMEA, and our India hub, and build the regional leadership layer that runs them day to day.
• Lead the conversion. Move existing PS Solution Architects, Solution Analysts, and Engagement Managers into the new roles – defining the career paths, success metrics, and ways of working that make embedded ownership stick.
• Design the coverage model. Decide where named, in-region resources make sense for the largest accounts and where pooled coverage serves the rest. Own capacity planning, staffing, and utilization across the portfolio.
• Own the architecture standards. Set the data model conventions, governance framework, and reference architectures that every account's Live boards, Spotter agents, and Data Apps are built on – so every deployment is secure, scalable, and consistent, not a one-off.
• Own delivery excellence. Set the outcome-based delivery methodology your AI Deployment Managers run on – scope, schedule, milestones, and documented results tied to measurable business value rather than hours delivered.
• Raise the bar on the build. Ensure your AI Outcomes Analysts ship production-ready work – semantic models, Spotter configurations, performance tuning, and migrations from legacy BI platforms like Tableau, Qlik, and Power BI.
• Be the executive escalation point. When a deployment hits a wall – complex data models, security design, performance at scale, or a delivery at risk – your team is the answer, and so are you when it matters.
• Lead strategy for the most complex accounts. Take executive point on enterprise-scale, multi-team, high-revenue engagements where architecture and delivery decisions carry the most risk.
• Own the portfolio view. Aggregate what's working and what's breaking across accounts, and translate it into product feedback and roadmap input for Thought Spot's Product and Engineering teams.
• Partner with AI Outcomes Managers on retention and growth. Your teams' delivery quality drives adoption, renewal, and expansion. Work hand in hand with the AI Outcomes Manager organization to protect GRR, grow NRR, and surface follow-on opportunities in every account.
• Make it scale. Turn bespoke architecture and delivery decisions into reusable patterns, playbooks, and AI-assisted workflows, so the practice gets faster and more consistent account to account.

What You Bring:

• A builder of delivery organizations. 12+ years in solution architecture, technical consulting, or professional services, including 5+ years leading multi-team technical delivery organizations – architecture, implementation, and delivery management – not just a single team or a book of accounts.
• Glob…