Founding Head of Product/AI

Chief Rebel is building the intelligence layer for small-business acquisition finance. Today, lenders repeatedly reconstruct the same analysis for every acquisition: financial normalization, valuation, debt-service capacity, buyer risk, deal structure, and credit underwriting. After close, much of that intelligence gets trapped in static files. Chief Rebel turns that fragmented process into a living credit record. Before close, we help lenders understand what a business is worth, whether an acquisition is financeable, and how the deal should be underwritten. After close, we keep the financial data connected so lenders can monitor how the business is actually performing. Over time, this creates something that doesn’t really exist today: a longitudinal dataset connecting the business, buyer, purchase price, capital structure, underwriting decision, and actual outcome. We have paying customers and funding. The Role We’re looking for a Founding Head of Product/AI to build the intelligence engine. You’ll own the product, strategy, models, data architecture, and applied AI systems that transform messy private-company financial data into trusted underwriting intelligence. This is a hands-on founding role with room to grow into leadership quickly. You’ll build production systems yourself, work directly with our CEO, spend time with lenders and underwriters, and eventually recruit and lead our Product/AI organization. Your core challenge is: Given this business, this buyer, this purchase price, and this capital structure, what’s likely to happen? What You’ll Build You’ll own Product and AI, using an ML-oriented lens across areas including: Financial normalization across accounting, banking, tax, and transaction data Document intelligence for tax returns, financial statements, valuations, credit files, and acquisition docs Models for valuation, cash flow, DSCR, risk assessment, and acquisition underwriting AI-assisted underwriting and credit memo generation Anomaly detection and financial quality assessment Post-close monitoring and early-warning signals Models that connect underwriting assumptions to actual performance Longitudinal datasets linking transactions to repayment, default, growth, and resale outcomes Model evaluation, explainability, auditability, and human-in-the-loop workflows Data infrastructure designed to compound our intelligence with every transaction You’ll work closely with our CEO and customers on the product, platform, integrations, security, and production infrastructure required to deploy these systems inside financial institutions. What You Bring We’re looking for someone who’s built sophisticated ML or AI systems in financial services and understands that underwriting isn’t simply a prediction problem, but a product and vision challenge. Strong candidates will have meaningful experience in several of the following: Credit, lending, underwriting, or risk Commercial banking or SMB lending Applied machine learning and predictive modeling Fintech or banking infrastructure Accounting and banking data LLMs and document intelligence Risk scoring and decision systems Model explainability and evaluation Human-in-the-loop ML Regulated or high-stakes ML environments Experience building credit or underwriting models with real performance or repayment outcomes is particularly interesting to us. What Matters Most You build. You’re deeply technical and still want to write code, train models, evaluate systems, and ship production software. You understand financial data. You’re comfortable with messy, incomplete, contradictory information and know how to turn it into structured intelligence. You have strong ML judgment. You know when to use an LLM, traditional ML, deterministic financial logic, or human review. You care about explainability. A lender needs to understand why the system reached a conclusion and trace it back to the underlying information. You think like an owner. You want meaningful ownership, ambiguity, customer exposure, and responsibility for building a company, not just a model. Why This Is Interesting Most fintech companies have access to a snapshot. We have the opportunity to capture the entire transaction arc: Every acquisition creates another transaction record. Every month after close gives us additional performance data. Eventually, we know the outcome. The opportunity is to build a learning system where every transaction makes Chief Rebel better at understanding the next one. What Success Looks Like Over the first 12 months, you’ll help us: Own product roadmap definition and delivery Deploy underwriting intelligence with lender design partners Process hundreds of real acquisition loan files Automate meaningful portions of acquisition underwriting Build robust financial and document normalization systems Launch post-close monitoring and risk signals Establish the first outcome-linked acquisition dataset Develop rigorous model evaluation and explainability infrastructure Recruit the initial AI/ML team, driving a ML-informed strategy Who You’ll Work With Our CEO has lived the workflow we’re rebuilding, including acquiring and exiting an $8M-revenue business through SBA 7(a), brokering more than $26M in transactions, and advising more than 100 business acquisitions. You’ll work alongside our CEO with clear ownership of Chief Rebel’s AI/ML, underwriting intelligence, and data advantage. Compensation and Ownership $150,000 - $200,000 base + 5.0% - 12.0% equity, depending on experience, commitment, and fit. We’re looking for someone who wants to build the intelligence foundation for how private businesses are underwritten and financed. If you’ve built ML systems in credit, lending, banking, underwriting, or financial risk and want to build something from the ground up, we want to talk. #J-18808-Ljbffr Chief Rebel