The AI Outcomes Architect owns the overall technical architecture across a portfolio of customer accounts. You set the standards, run the design reviews, and define the roadmap that every Liveboard, Spotter agent, and Data App is built on – so what an AI Outcomes Analyst ships is secure, scalable, and consistent, not a one-off. You will work closely with the AI Outcomes Manager, who owns the customer relationship, the AI Deployment Manager, who owns the delivery timeline, and the AI Outcomes Analyst, who owns the hands-on build – you are the technical backstop for all of them.

What You'll Do:

• Own the technical architecture. Set the overall architecture, data model standards, and governance framework that every account's Liveboards, Spotter agents, and Data Apps are built on.
• Run architecture and design reviews. Proactively review deployments across your portfolio of accounts – data model health, performance, security – and catch risk before it becomes a production issue.
• Set the technical roadmap. Define the best practices, reusable patterns, and technical playbook that AI Outcomes Analysts and AI Deployment Managers build from, account to account.
• Be a guide to the hardest technical problems. Be the escalation point when a deployment hits a wall an AI Outcomes Analyst can't get past alone – complex data models, security design, or performance at scale.
• Mentor and technically guide AI Outcomes Analysts. Review their semantic models and technical designs, share patterns that work, and build their capability so the whole team levels up.
• Lead technical strategy for the most complex accounts. Take point on enterprise-scale, multi-team, high revenue engagements where the architecture decisions carry the most risk.
• Own the technical portfolio view. Aggregate what's working and what's breaking across accounts, and translate that into product feedback and roadmap input for ThoughtSpot's product and engineering team.
• Partner across the AI Outcomes and other internal cross-functional teams. Work closely with ThoughtSpot’s AI Outcomes Managers, AI Deployment Managers, AI Outcomes Analysts, Product, and Engineering teams to keep every account's architecture sound as it scales.
• Champion best practices and governance. Build and maintain the standards, reference architectures, and design patterns that keep every deployment secure, performant, and consistent.

What You Bring:

• Customer-facing by nature. 8-10 years in solution architecture, technical consulting, or a similar senior, customer-facing technical role – you move between business stakeholders and deep technical work effortlessly, and you've done it long enough to know where things usually break.
• Delivery-tested at scale. You've architected and delivered complex data and analytics implementations across multiple enterprise accounts, ideally inside a SaaS or enterprise BI environment – you know what "production-ready at scale" actually looks like.
• Platform fluent. You're expert-level across BI tools like Tableau, Qlik, Power BI, Looker, Sigma and data platforms like Snowflake, Databricks, Redshift, Google BigQuery – and you can evaluate a new one fast.
• Deep in data and semantic modeling. Expert-level SQL and data/semantic modeling skills, with strong command of data warehousing ecosystems, schema design (OLTP vs. OLAP, star/snowflake, etc.), and security/governance patterns at enterprise scale.
• A force multiplier. You've mentored or technically guided other builders before – reviewing their work, sharing patterns, and raising the bar without taking over the build.
• A good internal partner. You've worked closely with Sales, Product Management, and Engineering, and you know how to bring the right people in at the right time.
• Consultative instinct. You ask before you architect. You listen for the outcome behind the request, and you know when to challenge a customer's technical assumptions rather than just build to spec.
• Bachelor's degree in a relevant field; advanced certifications in relevant technologies and platforms are a plus.

AI Mindset for All Spotters

At ThoughtSpot, we believe AI is a necessary and essential part of how we work. Every role, across every team, is expected to be fluent and comfortable with using AI to do their best work.

All Spotters are expected to experiment with ThoughtSpot’s AI tools (like Spotter and SpotterViz) and leading industry LLMs to streamline workflows, enhance output, and uncover new insights. Whether drafting content, analyzing data, or summarizing documents, AI is a daily partner. We value curiosity, openness to learning, and thoughtful application of AI to create real value. Training and resources are provided so every Spotter can confidently create with AI.