Finance AI & Automation Lead

Role Overview

• You’ll turn Finance into a real-time, self-service platform by building:
• AI-powered workflows that automate reporting, forecasting, close, reconciliation, variance analysis, and more.
• Event-driven data pipelines from ERP and financial systems into cloud warehouses (Snowflake/BigQuery), paired with dbt, orchestration, and CI/CD best practices.
• Natural-language access to Finance data—so business partners can get answers instantly, without relying on analysts.
• Self-service tools for budgeting, scenario planning, accruals, opex/capex, working capital, and headcount planning.
• Strong, built-in governance: lineage, documentation, approvals, and audit trails.
• You’ll own the Finance data architecture—modeling P&L, balance sheet, cash flow, and segment reporting for real-time use and AI interoperability, while enforcing data quality, testing, and access controls.
• And you’ll drive automation across core cycles (close, FP&A, revenue, procurement), delivering measurable improvements in accuracy, speed, and manual work elimination.
• Close partnership with leadership You’ll work directly with the CFO and leadership team to define OKRs, prioritize automation opportunities, and align solutions to business needs across origination, servicing, and marketplace operations.
• You’ll operate with autonomy and accountability—owning problem definition through delivery.
• You will partner closely with the centralized Technology team to leverage shared AI platforms, agent frameworks, and governance standards while delivering Finance-specific solutions. Success is measured by outcomes: automation %, cycle-time reduction, forecasting improvements, and stakeholder satisfaction.

Requirements

• 3+ years of experience building finance-oriented data or automation systems (analytics, FP&A engineering, data engineering, or similar)
• Deep SQL and data modeling expertise; advanced Python for automation, data pipelines, and AI agent development
• Hands-on experience with warehouses (Snowflake/BigQuery/Redshift), dbt, and orchestration tools
• Experience building LLM-powered applications, including prompt engineering, RAG pipelines, agentic AI frameworks, APIs, and natural-language interfaces
• Familiarity with AI orchestration frameworks such as LangGraph, LangChain, or similar, and experience integrating LLM APIs (OpenAI, Anthropic, AWS Bedrock, etc.) into production workflows
• Familiarity with workflow orchestration tools (Airflow, Prefect, Temporal, n8n, or equivalent)
• Familiarity with cloud-native architectures and services, preferably on AWS
• Strong understanding of data governance, quality frameworks, and systems integration (ERP, HRIS, ATS, CRM, planning tools)
• A product mindset: you ship, iterate, and build solutions people actually adopt.
• Experience in mortgage/real estate tech or marketplace environments is a bonus, but not required.

Tech Stack

• Airflow
• Amazon Redshift
• AWS
• BigQuery
• Cloud
• ERP
• Python
• SQL

Benefits

• Medical, Dental, Vision
• FSA
• Life + STD/LTD
• Paid holidays + 19 days PTO (28 paid days/year)