Plaid operates a financial data network and API platform that lets businesses connect to financial institutions and build financial experiences. Its products support account and identity verification, real-time balance and transaction data, investment and liability data, income and underwriting workflows, fraud and AML risk checks, and multi-rail bank payments. It serves developers, businesses, financial institutions, platforms, lenders, banks, and consumer-facing financial-product providers.

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Skills

Agentic Systems Ai Strategy Api Communication Cross-Functional Collaboration Data Platform Embeddings Fintech Llm Machine-Learning Model Evaluation Model Training Platform Development Product Management Representation Learning Responsible Ai Risk Roadmap Stakeholder Management

Candidate Availability

Hybrid · San Francisco · Required

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

As a Product Manager on the AI Foundations team, you will drive Plaid's AI strategy by building the data and intelligence layer that powers smarter financial experiences. You will work across engineering, data science, and research to develop scalable AI systems, from core embeddings and representation learning to applied model integrations that enhance developer and consumer outcomes.

Requirements

8+ years of product management experience leading AI/ML or applied intelligence products from concept to production with measurable impact.
Deep technical fluency in how modern ML systems are trained, evaluated, deployed, and monitored.
Strategic and executional range, including defining long-term AI vision while delivering near-term experiments, prototypes, and launches.
Experience building scalable developer or data platforms through well-designed primitives, APIs, and frameworks.
Strong communication and influencing skills across technical and non-technical audiences.
Commitment to responsible AI and transparency, especially in regulated or high-trust domains.
Hands-on production experience with LLMs, embeddings, or agentic systems is nice to have.
Familiarity with applied AI in regulated or high-trust domains such as fintech, identity, or risk is nice to have.

Responsibilities

Define the strategy, roadmap, and success metrics for the core AI and data foundation.
Partner with Engineering and Data Science to design scalable AI systems, from model training and evaluation pipelines to APIs.
Drive initiatives from concept to production, balancing rapid experimentation with reliability, transparency, and responsible AI practices.
Work closely with research, platform, and product teams to embed AI capabilities across products and the developer platform.
Use metrics, model performance data, and customer feedback to validate impact and inform prioritization.
Translate complex AI concepts into clear narratives and tradeoffs for technical and non-technical stakeholders.

Benefits

Medical insurance
Dental insurance
Vision insurance
401(k)
Equity