Founding AI Engineer

Stott and May; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

Stott and May is seeking a Founding AI/ML Engineer to drive the development of a groundbreaking AI solution for institutional real estate firms. You will be responsible for the full AI stack, from LLM orchestration to building robust production AI infrastructure.

The ideal candidate has experience building production AI systems and a strong Python/backend foundation, with a proven track record in working with LLMs and agile startup environments. This role offers massive ownership and the chance to shape the technical architecture from the ground up.

Qualifications

• Experience building production AI systems required.
• Strong foundations in Python and backend development.
• Experience with large language models (LLMs) and retrieval-augmented generation (RAG).
• Ability to work in startup environments with a high degree of ownership.

Responsibilities

• Own the AI stack end-to-end.
• Build and orchestrate LLM systems.
• Develop retrieval systems and agentic workflows.
• Establish production AI infrastructure.

Skills

Production AI systems

Strong Python/backend foundations

Experience with LLMs

Experience with RAG

Experience with agents

Workflow orchestration

Startup mentality

High ownership

Job description

Please note! No Visa sponsorship available now or in the future. ( Including F1 OPT)

A fast-growing AI startup transforming how institutional real estate firms operate is hiring a Founding AI/ML Engineer. The product is already being used by major commercial real estate operators managing billions in assets.

You’ll own the AI stack end-to-end:

• LLM orchestration
• RAG + retrieval systems
• Agentic workflows
• Production AI infrastructure

Looking for engineers who have:

• Built production AI systems
• Strong Python/backend foundations
• Experience with LLMs, RAG, agents, or workflow orchestration
• Startup mentality and high ownership

This is a true 0-1 opportunity with massive ownership, direct founder collaboration, and the chance to shape both the technical architecture and AI culture from day one.

Small team. Big technical problems. Real-world AI deployment.