Founding Engineer

About the role

Who We Are

The next frontier of applied AI isn’t another chat window embedded in a system of record. It’s systems that can perceive, reason about, and act on the physical world. Restaurants are a $1.5T industry that runs almost entirely on tribal knowledge and guesswork, and where the data that matters has never before been captured cleanly.

At Marble, we’re building the first agentic operating system for physical industries, starting with multi-unit restaurant groups.

We've spent decades in this industry and have shipped AI/ML systems at scale for some of the largest institutions on the planet. That means we speak the customer's language and are building workflows around processes we already understand deeply. In less than four months, we signed 150+ restaurants across the US, Canada, and Europe, and have grown 25% week over week for three months and counting. We're backed by Y Combinator and a host of incredible investors, angels, and operators.

The Role

We're looking for a product-minded founding engineer who will challenge us, push the boundaries of what's possible, and shape how operators experience our product. Engineers at Marble are not ticket-takers: you'll drive the product roadmap, speak with customers, sell the product, and have a voice in strategic decisions from day one.

We have a strong preference for individuals with a founder tilt: people who have founded something, want to found something, or simply can't stop building.

What you'll work on:

- Build the full lifecycle: Architect and ship customer-facing functionality from 0-to-1, from the agent that drafts a purchase order to the interface a manager approves it in.

- Own the agent harness: Build the systems that let models reason over operational data, use tools, and carry work through to completion. Own context management, orchestration, persistent state, and human approval flows for agents making purchasing and inventory decisions with real dollars attached.

- Solve hard data problems: Backend APIs, integrations (POS, accounting, payroll), background jobs, and pipelines that turn invoices, recipes, vendor catalogs, and stock counts into clean ground truth.

- Make agents dependable: Build evaluations from real operator workflows, trace failures across model and tool interactions, and improve how agents recover or escalate when they get stuck. Use production evidence to choose models and improve task completion, latency, and cost.

- Drive user experience: Work across backend services and React interfaces to deliver complete features. Bridge the gap between "working code" and a product operators want to open every morning.

- Learn from production: Take customer feedback and real-world behavior and turn it into improvements in accuracy, usability, speed, and cost.

Requirements

- Can be in office 5 days/week in New York City

- A technical spike: Deep, hands-on ability in at least one of: LLM/agentic applications, backend and data systems, or product engineering in React. Strong fundamentals in Python or JavaScript/TypeScript, with willingness to become productive in both.