Product.ai Offices

Build and own production agent systems, including orchestration loops, tool use, retrieval-augmented generation, evaluation gates, and MCP servers. Design reliable control flow with retries, timeouts, state management, grounding, and failure recovery. Develop regression corpora and judge-based gates to determine whether agent-generated code and content can ship safely. Maintain APIs under malformed or hostile inputs and evolving system rules while delivering both architecture and deployed code.

Build integrations directly with AI shopping agent and developer customers, ensuring they work in production. Own API and MCP pricing and packaging, close the first paying accounts, support onboarding, and bring customer learning back into the product. This role combines hands-on integration engineering, technical sales, account support, and commercial ownership. The engineer will also help define the operating charter and playbook for future forward deployed hires.

Own the distributed serving and data infrastructure powering globally served pages and governed multi-agent build loops. Design caching, indexing, rebuild, reliability, observability, performance, and invariant-based enforcement systems. Take end-to-end responsibility for correctness, uptime, failure handling, latency budgets, and production incidents without a dedicated operations team. The role requires independently modeling complex systems, proving correctness under load, and evolving infrastructure as AI capabilities change.