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Henry AI

AI copilot for CRE deal generation

Director of Enterprise - DUS Lenders

Account ExecutiveConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • At least 5 years working directly for Fannie Mae or Freddie Mac, or at a DUS lender.
  • Deep relationships across agency lending, including connections with production and credit leaders at major DUS lenders.
  • In-depth knowledge of sizing, underwriting, credit memos, loan packages, and agency review requirements.
  • Ability to run a deal from the first conversation through pilot, scope, and signed contract independently.
  • Founder-level ownership and willingness to take responsibility for work across organizational boundaries.
  • Must be in New York City or willing to relocate for in-person work five days a week.
  • Willingness to work 60 or more hours per week.

Responsibilities

  • Own a named list of the largest DUS lenders and the path to firm-wide adoption at each.
  • Run deals end to end, including discovery, pilots, pricing, legal, security review, and procurement.
  • Design proofs of concept, agree on success criteria with customers, and scope rollouts without handing off to a solutions team.
  • Build and maintain senior relationships with heads of production, chief credit officers, originators, and underwriting leads.
  • Translate knowledge of DUS lender agency-deal workflows into clear product feedback.
  • Own account strategy and involve the CEO at appropriate moments while co-piloting the largest accounts.
  • Build the DUS lender playbook for landing additional lenders.

Desired Qualifications

  • Experience closing enterprise software deals, especially with lenders or financial services companies.
  • Experience working across more than one DUS lender.
  • Experience working at a Series A to C startup.

About the Company

Henry AI

AI copilot for CRE deal generation

Henry AI builds an AI-powered platform for commercial real estate brokerages that acts as an AI copilot to automate workflows. It ingests underwriting or capital models, combines a brokerage’s internal data with external sources via Google’s Gemini, and automatically generates financial models, offering memorandums, BOVs, marketing teasers, and underwriting models into polished deal decks in minutes. The product is designed with CRE-specific workflows and deep data integration, and is already used by several top national firms. The goal is to scale automated workflows across CRE brokerages to close deals faster and free up brokers to focus on client relationships and deal execution.

Company size
11-50
Company stage
Series A
Total funding
$20.9M
Headquarters
New York City, United States
Founded
2024

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