Residential Mortgage Loan Underwriter (Contract)

JazzX AILos Altos, CA
Remote

About The Position

As a Part‑Time Residential Mortgage Loan Underwriter Consultant at JazzX AI, you will leverage your deep expertise in underwriting to build AI-technology to support mortgage underwriting activities. You will work closely with engineering, and product teams to convert real-world underwriting decisions into robust AI logic. This is a contract role with an initial duration of 6 months, with the potential for extension up to 12 months. JazzX AI is defining the future of enterprise work by building AI-native digital workers. They focus on transforming enterprise reality into institutional intelligence, starting with lending and due-diligence workflows. The company is backed by SAIGroup, a private investment firm with $1B committed to AI-powered enterprise software companies.

Requirements

  • 4–10 years in residential mortgage underwriting at a senior or specialist level.
  • Deep, hands-on knowledge of Fannie Mae DU and/or Freddie Mac LP guidelines.
  • Proven ability to assess borrower credit, income, assets, and collateral with accuracy and consistency.
  • Exceptional verbal and written skills to articulate underwriting logic and decision processes.
  • Comfortable in an iterative environment, providing structured feedback to product and engineering teams.

Nice To Haves

  • Experience at large retail or independent mortgage lenders (e.g., Wells Fargo, Rocket Mortgage, Chase).
  • Background in manual underwriting, AUS overrides, or secondary market delivery.
  • Familiarity with post-closing QC, servicing reviews, and secondary market delivery processes.
  • Prior involvement in technology or automation initiatives within mortgage operations.

Responsibilities

  • Underwrite a variety of residential mortgage loan files (purchase, rate‑term refinance, cash‑out refinance) per Fannie Mae DU and Freddie Mac LP guidelines.
  • Document underwriting rationale, risk profiles, and exception handling.
  • Deconstruct end-to-end underwriting workflows—from borrower qualification and income/asset verification to AUS findings and final approval.
  • Identify critical decision points and edge cases crucial for AI modeling.
  • Blind-test AI-generated underwriting recommendations against manual assessments.
  • Provide granular feedback to engineering teams to fine-tune decision rules and confidence thresholds.
  • Create clear, actionable guides on complex topics (e.g., compensating factors, manual AUS overrides, GSE compliance).
  • Host virtual workshops or Q&A sessions to transfer domain knowledge to cross-functional teams.
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