AI Product Manager

Mulligan Funding•San Francisco, CA

79d•$170,000 - $250,000•Onsite

About The Position

Mulligan Funding is seeking an AI Product Manager to join their AI-first initiative. This hands-on role involves leading discovery and design for active AI projects, collaborating with business teams, and managing execution with engineering partners. The ideal candidate will thrive in ambiguous environments, transforming complex problems into clear designs by mapping and redesigning daily workflows using modern AI tools. Reporting to the AI Product Director, this position offers high autonomy and is perfect for an early-career product manager aiming to rapidly build AI expertise and grow with the company. Mulligan Funding is replacing legacy small business lending with AI-driven decisioning, leveraging proprietary data and deep risk expertise. Production-grade AI agents are already in use, and the company is expanding this approach across various departments.

Requirements

3-5 years of experience in product management, product analysis, or a closely related role with direct exposure to AI-enabled products.
Demonstrated ability to lead structured discovery with domain experts, extract precise process intelligence, surface undocumented edge cases, and translate findings into a clear design brief.
Experience authoring clear written product artifacts (process maps, design briefs, requirements documents, specifications).
Comfortable managing ambiguity and structuring undefined problems without waiting for direction.
A willingness to learn partner management and hold partners to a specification is essential.
Bachelor's Degree in Business, Computer Science, Engineering, Economics, or a related field.

Nice To Haves

Prior experience at an AI-native fintech, lending company, or high-velocity product environment.
Candidates who have only worked in waterfall delivery environments or large enterprise software teams are unlikely to have the transformation energy this role demands.
Experience coordinating with external engineering vendors or technology partners.
Master's degree.

Responsibilities

Lead structured discovery sessions with Subject Matter Experts (SMEs) to map current processes, identify pain points, and understand exceptions.
Quantify current state metrics (cycle times, error rates, manual touchpoints) to establish a baseline for impact assessment.
Identify process edge cases, informal workarounds, and undocumented exceptions.
Test design hypotheses during discovery to challenge assumptions.
Translate current state intelligence into an AI transformation design brief that reimagines the process from scratch.
Collaborate with the AI Product Director to author a detailed solution design brief defining AI capability, inputs, outputs, logic, QC framework, and acceptance criteria.
Conduct research to identify specialist engineering partners with relevant track records.
Produce a clear go/no-go recommendation with supporting rationale.
Manage the working relationship with the specialist engineering partner throughout the build cycle.
Review partner outputs against the design brief and acceptance criteria.
Facilitate the review-feedback-refine loop between the engineering partner and internal stakeholders.
Design the QC framework, including human review processes, deterministic checks, and LLM-as-judge rubrics.
Collaborate to establish evaluation rubrics, golden datasets, and accuracy thresholds.
Ensure AI agent outputs are reviewed by the QC function before being shown to end-users.
Coordinate the shadow run period for side-by-side comparison of AI output and current processes.
Work with the functional head to build the end-user adoption plan.
Track post-deployment metrics against the pre-implementation baseline and gather feedback for model refinement.