Deployment Strategist, Enterprise AI Fintech (NYC/SF)

Lavendo•New York, NY

6d•$140,000 - $240,000•Hybrid

About The Position

This role is with an AI-native software company building the operating system for mortgage servicing. The company has raised $150M in Series D funding at a $2B+ valuation. The platform was built around real operations, integrating loan records, money movement, workflows, task management, and audit trails, with native AI agents operating within its permissions and controls. The company has already secured over $200M in contracted ARR within its first six months and has institutions managing a significant portion of U.S. mortgages under contract to use its platform. The mission is to replace legacy mortgage systems with software where AI can perform real work, adhering to the context, controls, and audit trails required by regulated finance.

Requirements

3-6 years in strategy consulting, investment banking, private equity, hedge funds, or high-growth startups
Undergraduate degree from a top university
Proof that you built or defined playbooks, tooling, and processes from scratch
Hands-on use of AI tools and coding agents
Hybrid in NYC (Union Square) or SF (SoMa), 3-4 days in office
Domestic travel of roughly 10-20%, might be higher during critical phases

Nice To Haves

High agency: you see what needs to happen and start, without waiting for a playbook
Ownership: you care about the outcome, not just your deliverable
First-principles thinking: you break down unfamiliar problems and decide from evidence
Range: you can brief an executive in the morning and debug a data issue in the afternoon
Fast learning: you pick up complex systems and regulatory detail quickly
Judgment: you move fast while protecting correctness, compliance, and client trust
Builder instinct: you create structure where none exists

Responsibilities

Own deployment workstreams from discovery through configuration, migration, launch, and adoption
Map client workflows, find platform gaps, and align client leadership on priorities and sequencing
Investigate data across the platform, client operations, and capital-partner records
Work onsite with specialists in escrow, foreclosure, loss mitigation, and cash operations
Turn operational findings into product and engineering requirements
Coordinate engineering, product, compliance, executives, and external partners without disrupting live operations
Build reusable playbooks, internal tools, and AI workflows for the whole team
Stay accountable after launch for adoption, performance, and business results