Senior Security Engineering

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.

In-Office at ThoughtSpot
Spotters are expected in-office 3+ days per week to be part of the energy of their local team. Being in-office is our default way of working, with flexibility available where it's genuinely needed.

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. That’s why we build products that make asking and answering data questions as natural as having a conversation.

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.

Complex data problems need many perspectives, not just one. ThoughtSpot is the Agentic Analytics Platform that empowers every enterprise to transform insights into action, on a mission to make the world more fact driven. When paired with our culture of Trust, Customer Obsession, Innovation and Intensity, ThoughtSpot cultivates a respectful culture that pushes norms to create world-class products.

We're looking for a Security Engineer to join our AI Platform Security team. It is a high-ownership, low-oversight role for an application/product security generalist who has already done the work and is ready to set direction rather than follow it. You'll make real risk calls, push back on engineering leadership when the data supports it, and be accountable for the areas you own while helping to shape how this team operates as it scales.

Own end-to-end security for an assigned portfolio of products: design reviews, threat modeling, risk acceptance, and driving high-severity findings to closure
Drive shift-left adoption across the SDLC through pipeline gates, guardrails, paved-path patterns, and developer enablement
Lead the team's AI/LLM security practice: assessment methodology, testing approach, and applied frameworks for agentic and model-backed features
Communicate risk and program health to engineering and executive leadership through metrics, reporting, and clear written narratives

Experience in security engineering, application security, offensive security, or a closely related technical discipline
Deep, demonstrated knowledge of vulnerability classes and exploitation: injection, authentication and session flaws, access control, deserialization, SSRF, and their real-world variants
You will produce standards, risk narratives, executive reporting, and researcher-facing correspondence
Comfort operating with ambiguity and building structure where none exists yet

Hands-on depth with security tooling such as Snyk, Burp Suite, DAST, or SAST platforms, including tuning and integration rather than just usage
Applied understanding of AI/LLM security risks: prompt injection, insecure tool use, context and data leakage, model supply chain