AI Outcomes Architect

ThoughtSpot 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 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.

In-Office at ThoughtSpot

Spotters are expected in-office 3+ days per week to be part of the energy of their local team. Momentum compounds when we're in the room together with faster decisions, sharper problem-solving, and the kind of peer learning that doesn't happen over a screen. Being in-office is our default way of working, with flexibility available where it's genuinely needed.

About ThoughtSpot

The world’s most innovative companies turn to ThoughtSpot’s AI-Powered Analytics to put data in the hands of everyone, from the C-suite to the frontline. With simple, natural language search and AI, anyone can ask questions, discover insights, and act with confidence. Unlike legacy tools that sacrifice performance for complexity, ThoughtSpot is intuitively designed for every business user while being built to handle the most complex, large-scale data, wherever it resides. This unique combination of speed and simplicity is why enterprise leaders trust ThoughtSpot to transform decision-making into a truly data-driven culture.

At ThoughtSpot, we’re a curious, data-driven bunch. We believe the world works better when everyone has access to facts. That’s why we build products that make asking and answering data questions as natural as having a conversation.

Mandatory and Required Skills for All ThoughtSpot Roles

Spotters are expected to demonstrate AI literacy and workflow integration to include to ability to:

• Comfortably and confidently integrate artificial intelligence into their daily workflow to increase productivity and quality.
• Hands-on experience to leverage AI tools (industry-leading LLMs) to increase productivity, automate routine tasks, and improve work quality.
• Speak to the experience of using AI for research, content creation, and document summarization while maintaining ownership of judgment and final decisions.
• Write effective prompts to get the most 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, and discernment defines the AI mindset, and it’s required for every role at ThoughtSpot.

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.

ThoughtSpot for All

At ThoughtSpot, diverse teams build better products. Complex data problems need many perspectives, not just one. We welcome different backgrounds, identities, and experiences, and we work to create a place where everyone can be themselves and do their best work. If this role excites you and you believe you’re a strong match, we encourage you to apply.

What Makes ThoughtSpot a Great Place to Work?

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