Staff Product Manager - AI Foundations

Responsibilities

• AI Platform Vision: Define the strategy, roadmap, and success metrics for Plaid’s core AI and data foundation, enabling smarter, more adaptive financial products across the ecosystem.
• System Development: Partner with Engineering and Data Science to design scalable AI systems, from model training and evaluation pipelines to APIs that deliver intelligence at scale.
• Product Execution: Drive initiatives from concept to production, balancing rapid experimentation with reliability, transparency, and responsible AI practices.
• Cross-Functional Collaboration: Work closely with research, platform, and product teams to embed AI capabilities across Plaid’s products and developer platform.
• Measurement and Iteration: Use metrics, model performance data, and customer feedback to validate impact, inform prioritization, and continuously improve outcomes.
• Communication and Alignment: Translate complex AI concepts into clear narratives and tradeoffs for technical and non-technical stakeholders, building shared understanding across teams.

Qualifications

• 8+ years of product management experience with direct 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, with the ability to engage confidently with engineers and data scientists.
• Strategic and executional range. Skilled at defining long-term AI vision while delivering near-term experiments, prototypes, and launches.
• Platform mindset and experience building scalable developer or data platforms through well-designed primitives, APIs, and frameworks.
• Strong communicator and influencer who can translate complex AI concepts into clear narratives and decisions for technical and non-technical audiences.
• Commitment to responsible AI and transparency, especially in regulated or high-trust domains.

Nice to Have

• Hands-on experience with LLMs, embeddings, or agentic systems in production.
• Familiarity with applied AI in regulated or high-trust domains such as fintech, identity, or risk.