About Discovered Labs

At Discovered Labs we work with $10M - $50M ARR companies to help them get more leads, users and customers from Google, Bing and AI assistants such as ChatGPT, Claude and Perplexity.

We approach marketing the way engineers approach systems: data in, insights out, feedback loops everywhere. Every decision traces back to measurable outcomes. Every workflow is designed to eliminate manual bottlenecks and compound over time.

High-level overview of our approach:

• Data-driven automation: We treat marketing programs like products. We instrument everything, automate the repetitive, and focus human effort on high-leverage problems.
• First principles thinking: We don't copy what others do. We understand the underlying mechanics of how search and AI systems work, then build solutions from that foundation.
• Full-stack ownership: SEO and AEO rarely work as isolated tasks. We work across the entire funnel and multiple surface areas to ensure we own the outcome and clients win.

The Team

We're a deeply technical team building the SpaceX of the AEO & SEO space. You'll work alongside engineers who have built fraud engines powering Stripe, Plaid, and Coinbase; developed self-driving car systems at Aurora; and conducted AI research at Stanford. We don't have layers of management. You'll work directly with founders who can go deep on architecture, code, and product.

This Role

We're looking for a Senior Engineer to own the development and delivery of some of our core product infrastructure. You'll work directly with the CTO to build client-facing dashboards, AI visibility tooling, and automated content and outreach systems.

This is a high-ownership, hands-on role. You'll take feature specs from idea to production, own the quality of your releases, and help us ship faster without sacrificing reliability. If you thrive on building products that matter, not just writing code, this is for you.

What You'll Do

• Build client-facing products: Design and ship deep analytics dashboards to uncover insights in AI search performance in a data-driven manner, all the way to mechanism interpretability of these LLMs.
• Develop AI-powered tooling: Extend our internal systems into public-facing products, including automated reporting and intelligent workflows.
• Own the full lifecycle: Take features from spec to production, monitor reliability, and iterate based on feedback. You own what you build.