Founding AI Engineer

The commercial real estate space is ripe for disruption. The industry has exploded in size and revenue, but still runs on fragmented CRMs, legacy loan systems, email, spreadsheets, phone calls, and document portals. Legacy players are struggling to adapt to an AI-native age, while lenders and brokers are constrained by manual work.

We’re going to change that.

We’re building an autonomous loan origination and processing platform that helps commercial real estate lenders move loans from intake through underwriting with no manual work. We’re:

• An experienced team used to shipping fast - with alumni and tech leads from Meta, LinkedIn, and Rippling.

• Backed by a16z through Speedrun.

• Working with multiple paid pilots, and moving quickly from customer conversations to production software.

The Role

We’re looking for a founding AI/ML engineer to build the intelligent systems at the heart of our product.

You’ll work directly with the founders and customers and own the full production loop: data, model selection and adaptation, evaluations, serving, monitoring, and iteration. You’ll turn messy, real-world financial information into reliable decisions and actions.

You'll:

• Build production AI systems for complex, high-stakes workflows

• Develop models and pipelines for understanding unstructured and structured financial data

• Design evaluation systems that measure quality, reliability, latency, and cost

• Build feedback loops that turn customer usage into better models and products

• Decide when to use foundation models, specialized models, deterministic systems, or a combination

• Ship constantly, observe real-world performance, and iterate with customers

• Establish the ML infrastructure and standards that future hires inherit

What We’re Looking For

• Evidence that you’ve shipped ML systems that real users touched

• Strong software engineering fundamentals beyond notebooks and prototypes

• Experience evaluating, adapting, and operating modern models in production

• Sound judgment about model quality, failure modes, latency, and cost

• Pragmatism: you use the simplest approach that reliably solves the problem

• Fluency with AI coding agents and the ability to use them without outsourcing your engineering judgment

• Live in San Francisco and are available to work in person with the team 5 days a week.

Experience with Python, PyTorch, model serving, LLMs, retrieval, document intelligence, or multimodal systems is helpful, but the ability to learn and execute matters more. You don’t need prior experience in lending or commercial real estate.