About this role
About the company Our client is building the attribution and experimentation layer for AI search. More and more buying decisions now start in AI assistants, yet most companies can't see how they show up there or connect that visibility to revenue. Our client uses large-scale simulations, agentic analysis, and deep integrations with customer data to turn AI search from a black box into a measurable growth channel that teams can optimize and allocate spend against. They are a seed-stage startup with $5M+ raised from Tier-1 VCs and a team of about 15, including 5 engineers. The engineering team also publishes original research on how LLM-driven search behaves. The role This is a backend-focused engineering role reporting directly to the CTO. Work is project-based and spans the product: building recommendation agents, reworking the database layer to cut latency on very large data ingestion, and running research experiments. Over time you'll take ownership of the parts of the product you know best. What you'll do Define and build product end to end, with full ownership from design through deployment and scale Design and build large-scale systems, data models, and infrastructure Tackle ambiguous, unsolved problems in AI search by running experiments and turning results into product Join customer calls from time to time, as every engineer on a small team does What we're looking for 4+ years of backend engineering experience You've built from zero to one: designed systems and databases from scratch or at an early stage, and your architecture and data decisions had real impact Strong fundamentals in system design and databases, with good judgment on when to move fast and when to build for scale You can break down large, ambiguous problems and own large t...