About the Role We are a small, product-focused team building an AI-powered B2B pricing platform that helps companies optimize pricing strategies—from packaging design and willingness-to-pay analysis to real-time deal guidance and discount governance. As the Founding AI Engineer, you will own the evaluation systems, feedback loops, and the LLM infrastructure that allow our pricing AI to earn trust and drive measurable revenue impact. This is a high-ownership founding-team role. Your work directly ties model outputs to revenue and compliance constraints in high-stakes B2B pricing decisions. You will ship to real customers from day one and own outcomes end-to-end.

What You'll Do - Build evaluation harnesses and benchmarks that use pricing outcomes as ground truth. - Systematize and automate expert review workflows currently performed manually. - Develop AI personas that simulate B2B buying committees and behavioral effects using usage data and call transcripts. - Automate persona training pipelines that are today manual. - Own LLM routing across providers (Anthropic, Google, etc.) with explicit cost, latency, and quality tradeoffs. - Maintain infrastructure and data residency boundaries (e.g., ensure EU model calls remain in the EU). - Extend the MCP server used by LLM agents—including customer-facing agents—so features are agent-driven. - Define "done" as when agents can drive features through MCP, not just when a UI renders them. - Work within a typed ontology of pricing entities so model outputs are structured and auditable. - Identify and remediate systemic latency, data

About the Role We are a small, product-focused team building an AI-powered B2B pricing platform that helps companies optimize pricing strategies—from packaging design and willingness-to-pay analysis to real-time deal guidance and discount governance. As the Founding AI Engineer, you will own the evaluation systems, feedback loops, and the LLM infrastructure that allow our pricing AI to earn trust and drive measurable revenue impact. This is a high-ownership founding-team role. Your work directly ties model outputs to revenue and compliance constraints in high-stakes B2B pricing decisions. You will ship to real customers from day one and own outcomes end-to-end.

What You'll Do - Build evaluation harnesses and benchmarks that use pricing outcomes as ground truth. - Systematize and automate expert review workflows currently performed manually. - Develop AI personas that simulate B2B buying committees and behavioral effects using usage data and call transcripts. - Automate persona training pipelines that are today manual. - Own LLM routing across providers (Anthropic, Google, etc.) with explicit cost, latency, and quality tradeoffs. - Maintain infrastructure and data residency boundaries (e.g., ensure EU model calls remain in the EU). - Extend the MCP server used by LLM agents—including customer-facing agents—so features are agent-driven. - Define "done" as when agents can drive features through MCP, not just when a UI renders them. - Work within a typed ontology of pricing entities so model outputs are structured and auditable. - Identify and remediate systemic latency, data