AI Product Director

Headquartered in San Diego, Mulligan Funding serves as a leading provider of working capital (Up to $5M) to the small and medium-sized businesses that fuel our country. Since 2008, we have prided ourselves on our collaborative, innovative, and customer-focused approach. Enjoying a period of unprecedented growth, driven by the combination of cutting-edge technology, human touch, and unwavering integrity, we are looking to add to our people first culture, with highly motivated and results-oriented professionals, to push the limits of what’s possible while creating value for all of our partners.
Mulligan is modernizing small business lending by replacing manual processes with faster, smarter AI decisioning. With 18 years of proprietary credit data and deep domain expertise, we have both the institutional knowledge and the technical infrastructure required to make this vision a reality.
We have already deployed production-grade AI agents in our core credit and underwriting workflows, delivering clear improvements in speed, accuracy, and consistency. We are now accelerating this effort across the rest of the business, bringing the same AI rigor to Sales, Customer Lifecycle, Finance, and Capital Markets while building an enterprise-grade product capability that scales.
The Chief Credit Officer serves as the Executive Lead for Mulligan's AI strategy, setting the vision and holding final product and engineering design authority.
We are seeking an AI Product Director to act as the CCO's senior strategic partner. In this role, you will help co-design product blueprints, translate strategic goals into precise technical specifications, lead delivery teams, manage external engineering partners, and partner closely with internal data teams.
You will oversee day-to-day product authority, technical execution, and operational delivery across all concurrent AI projects. Reporting directly to the CCO, this role offers high executive visibility and is structured to grow in scope as our AI capabilities mature.

Strategic Co-Design & Blueprint Authorship

- Co-Authoring Specifications: Partner closely with the CCO to translate strategic business objectives into detailed, buildable product and engineering blueprints for new AI initiatives.

- Regulatory & Compliance Integration: Ensure all AI design briefs explicitly account for relevant financial regulations (e.g., FCRA, ECOA / Regulation B, Fair Lending, Adverse Action rules) and model explainability standards prior to engineering builds.

- Process Intelligence Extraction: Conduct deep-dive discovery with Subject Matter Experts (SMEs) to map current processes and reimagine them through AI workflows — rather than simply digitising existing manual tasks.

Execution Leadership & Enterprise Alignment

- Product Authority: Serve as the day-to-day product authority across active initiatives — leading working sessions, maintaining delivery velocity, and, within approved design frameworks, making the technical trade-off decisions that keep execution moving.

- Cross-Functional Orchestration: Lead interdisciplinary teams comprising Data Science pods, internal Data Engineering and IT infrastructure leads, and functional business partners to ensure clean data pipelines and scalable infrastructure for AI models.

- PM Team Development: Build, coach, and manage a high-performing team of Junior AI PMs — establishing review standards for process mapping and design briefs before final executive sign-off.

Engineering Partner & Vendor Governance

- Technical Interface: Act as the primary product interface for external specialist engineering vendors. Evaluate architecture proposals and technical deliverables against Mulligan's specifications to ensure alignment.

- Vendor Principles: Enforce Mulligan's core partnership mandate: Mulligan authors the specification; partners never operate as unmonitored black boxes.

- Acceptance & Quality Criteria: Establish rigorous, verifiable acceptance metrics and output tests required for vendor milestone sign-off.

Quality Control & Evaluation Framework Ownership

- Pre-Build QC Design: Define robust Quality Control (QC) frameworks — including human-in-the-loop (HITL) workflows, deterministic rule checks, and LLM-as-judge evaluation frameworks — during Phase 1 discovery, before engineering builds begin.

- Benchmarking: Collaborate with Data Science leads to establish baseline evaluation rubrics, golden datasets, and accuracy thresholds prior to end-user rollout.

Stakeholder Engagement & Change Management

- Cross-Functional Sponsorship: Build trust across Sales, Credit, Operations, and Finance to ensure high end-user adoption and minimal operational disruption.

- Executive Visibility: Communicate clear programme metrics, delivery risks, and strategic trade-offs to key business leaders and executive management.

Required Experience & Education

- 8–12 years in product management, with a demonstrated track record of taking AI-enabled solutions from concept to production deployment — in environments where execution speed and design quality both mattered.

- Prior experience contributing to the design of AI solutions — not just managing their delivery. Candidates who have been in the architecture room, not just the delivery room, will thrive in this role.

- Strong executive presence — demonstrated ability to lead cross-functional meetings with functional heads and senior stakeholders, hold the room with authority, and represent product direction credibly without senior sponsorship present.

- Prior experience in fintech, lending, or a credit-adjacent product environment is strongly preferred. Candidates from large-company product management backgrounds without fintech or high-velocity product experience are unlikely to succeed in this role.

- Demonstrated ability to extract precise current state process intelligence from domain SMEs and translate it into AI transformation design briefs that reimagine the process rather than digitise the status quo.

- Experience managing specialist external engineering partners through a full build cycle — including reviewing technical deliverables against a product specification and holding partners accountable to defined acceptance criteria.

- Proven ability to coordinate multiple concurrent AI initiatives simultaneously without losing execution quality, design fidelity, or stakeholder confidence on any of them.

- Bachelor's Degree in Business, Computer Science, Engineering, Economics, or a related technical discipline is required.

- Master's degree is a plus, but evaluated secondary to a strong, verifiable track record of shipping production AI products in fintech.

Functional & Technical Skills

- Practitioner-Level AI Fluency: Deep familiarity with modern LLM architecture, agentic orchestration patterns, confidence-based decision routing, hallucination mitigation techniques, and golden dataset benchmarking — sufficient to co-author engineering blueprints, evaluate the soundness of partner-proposed architectures, and identify design gaps before they become build problems.

- Compliance & Model Governance: Working knowledge of credit regulations (FCRA, ECOA, Reg B), auditability requirements, and model governance in regulated industries.

- Process Discovery & Intelligence Extraction: Exceptional ability to interview domain experts, uncover undocumented edge cases, and translate current state intelligence into AI transformation design briefs that reimagine rather than digitize. Vision and ability to think outside of the box is mandatory

- Cross-Functional Communication & Executive Presence: The ability to lead rooms of functional heads, engineers, and data scientists with confidence and authority — holding the room credibly and driving decisions without senior sponsorship present. The ability to manage resistance to change from end-user communities without losing their trust. The ability to maintain executive confidence through honest, structured communication of programme health, risks, and trade-offs. This is a core competency of the role — not a background skill — and will be assessed directly in the interview process.

Mulligan Funding is an Equal Opportunity Employer (EOE) and takes great pride in building a diverse work environment. Qualified applicants are considered for employment without regard to age, race, religion, gender, national origin, sexual orientation, disability or veteran status.

A reasonable estimate of the base compensation range for this role is $250,000 to $350,000 per year. Total compensation may include base salary and other forms of compensation, such as an annual bonus as applicable. In determining compensation, Mulligan Funding considers a variety of factors, including but not limited to market data, relevant experience, skills, education, and certifications.