Founding AI Engineer

About this position

At Mondrio, we’re on a mission to build the future of pricing: agentic pricing management. We believe that monetization should be data-driven rather than a one-time exercise. It should evolve as products, markets, or sales motions change. Our AI-native platform equips companies to bring that pricing intelligence into strategy and deal decisions.
About Mondrio
Mondrio is a fast-growing Seed stage startup built on deep pricing experience from our founding team who have run over 150 pricing engagements. We’ve seen firsthand how companies struggle with pricing and leave money on the table. On the flipside, we’ve also seen firsthand how companies that make pricing a continuous capability thrive.

We have assembled our team of 8 (pricing experts and engineers) to deliver that capability. Our main hubs are San Francisco and Amsterdam, covering the North American and European markets. We believe owning those markets are key to building a category-defining company.

We're backed by renowned investors who've helped build generational companies, and we expect to grow the team 2-3x in the coming 12 months. Joining now means you’ll actively shape the product, the team, and the way we run engagements. If that kind of ownership and entrepreneurship sounds energizing rather than daunting, then this role is for you.

Mondrio's AI recommends prices, and expert Pricing Architects stay in the loop on the high-stakes calls. Your mandate is to build the evaluation systems and feedback loops that let the AI earn more of that trust.

This is applied AI on a problem where quality is measurable in customer revenue.

• Build evaluation for AI pricing recommendations: eval harnesses and benchmarks that use tracked pricing outcomes as ground truth. Expert review is manual today, and you make it systematic.
• Take AI personas further. They simulate B2B buying committees and behavioral effects such as new versus existing customers, grounded in usage data and call transcripts. Automate the parts of persona training that are still manual.
• Own LLM infrastructure: routing across current (Anthropic and Google) and future models, with explicit cost, latency, and quality tradeoffs.
• Maintain infra and data residency boundaries (e.g. model calls for EU customers must remain within the EU) as we add providers and scale up operations.
• Extend the MCP server that LLM agents, including our customers' own agents, use to drive the platform. A feature is done when an agent can drive it through MCP, not when the React component renders.
• Work within our typed ontology of pricing entities (Pydantic models for SKU, Proposition, Persona, Quote) so model outputs land in structured, auditable form.

• Model routing across Anthropic and Google has explicit cost and latency budgets, and the fail-closed EU residency guarantee covers every model call.
• Pinpoint systemic latency, data drift, or cold-start issues in the continuous pricing loop.
• Baseline current prompt and model outputs against our typed ontology to prepare for release-gating evals.
• Conduct code reviews and lead a technical session on advanced AI/ML patterns for the team.

• An eval harness runs on every model or prompt change, and the team trusts its benchmarks enough to gate a release on them.
• Manual steps in persona training now run as an automated pipeline built on the same usage data and call transcripts.

• Tracked pricing outcomes feed back into recommendation quality, so evals measure revenue impact, not proxy scores.
• Participate actively in interview loops to scale the engineering team and mentor mid-level engineers.

• 8+ years of engineering experience with strong and recent production LLM depth.
• You have shipped LLM-powered product features to production and owned them after launch.
• You have built evals and observability for LLM systems yourself. Running someone else's dashboard does not count.
• Strong communication skills to bridge the technical gap around non-deterministic engineering to less savvy clients and partners
• Product engineer…