Senior Engineering Manager

About the Role

ThoughtSpot is building a best-in-class product-led growth engine to transform how users discover, adopt, and expand with our AI-powered analytics platform. We're looking for a Senior Engineering Manager to lead the engineering team behind our PLG initiatives including our free trial experience, AI-powered onboarding, developer-focused offerings, and cross-platform plugins for Slack, Teams, Salesforce, and Microsoft/Google ecosystems.

This is a high-impact role. You'll own the technical execution of experiences that drive Product Qualified Leads, reduce time-to-value, and scale self-serve adoption across business users, analysts, and developers. You'll work closely with product, marketing, and go-to-market teams to ship fast, learn quickly, and build systems that enable continuous experimentation.

If you've built PLG products before, care deeply about developer experience, and thrive in high-velocity environments, this role is for you.

What You'll Do

• Build and lead a high-performing engineering team

• Hire, mentor, and grow engineers who can ship quality work quickly. Create a culture of ownership, transparency, and continuous learning. You'll manage the team directly and be responsible for their growth, performance, and engagement.

• Drive technical execution of PLG initiatives

• Own the roadmap for free trial onboarding, AI-powered personalization for easier onboarding, plugin ecosystem (Slack, Teams, Salesforce, Office), and developer-focused experiences. Ship features that directly impact PQL growth, activation rates, and user engagement.

• Build infrastructure for rapid experimentation

• Our biggest constraint is experimentation velocity. You'll architect systems that allow us to test hypotheses quickly - feature flags, A/B testing frameworks, and streamlined release processes. Push for shorter feedback loops and data-driven iteration.

• Integrate AI deeply into the product

• Embed LLMs into onboarding flows, personalize user journeys, and power our AI agents with smarter interactions. You'll make architectural decisions about prompt engineering, model selection, cost optimization, and reliability.

• Collaborate cross-functionally

• Work closely with Product Managers, Product Marketing Managers, and marketing leads to align on priorities, unblock execution, and communicate tradeoffs clearly. You'll influence product strategy, advocate for technical constraints, and ensure engineering has a strong voice in planning.

• Ensure operational excellence

• PLG depends on reliability. Trials must provision instantly, plugins must stay functional, and analytics must be accurate. Own monitoring, incident response, and the operational health of the PLG stack.

• Think strategically about the future

• Balance today's roadmap with long-term platform thinking. Identify technical debt that will slow us down, advocate for infrastructure investments, and position the team for the next phase of growth.

What You Bring

• 8+ years engineering experience, 3+ years managing teams (ideally managing managers)
• Deep PLG or self-serve product experience where you understand activation metrics, onboarding friction, and what drives conversion
• Full-stack technical fluency across frontend, backend, data pipelines, and integrations
• Hands-on experience shipping AI/ML features in production - prompt engineering, model APIs, cost/latency tradeoffs
• Track record building experimentation infrastructure that increased team velocity
• Strong cross-functional skills - you influence without authority and communicate technical constraints clearly
• Proven ability to ship on time while maintaining quality
• Comfort with ambiguity, iteration, and resourcefulness under constraint

Bonus Points

• Experience building developer-facing products or platforms
• Previous work at a high-growth SaaS or analytics company
• Familiarity with data instrumentation and analytics tools (Mixpanel, Amplitude, etc.)
• Experience with plugin ecosystems or integration platforms (Slack apps, Salesforce Lightning, etc.)
• Built systems that scale to millions of users