Director of Product Management

Visa•Foster City, CA

1d•$170,700 - $273,200•Hybrid

About The Position

We are seeking an experienced, hands-on Director of Product Management to join the FX and Cross-Border Product and Platform Architecture group. This is a horizontal product leadership role focused on enabling AI-driven product management practices, improving data-driven decisioning, and strengthening collaboration across product, platform architecture, engineering, data, analytics, operations, risk, compliance, finance, and business teams. The ideal candidate is a senior product leader who can influence across teams, create clarity in complex environments, and help the organization adopt AI in practical, responsible, and measurable ways. This person must be deeply hands-on with modern AI tools and act as an AI product enablement leader through “show, not tell” execution — demonstrating real use cases, building reusable workflows, educating teams, and embedding AI into day-to-day product management practices. This role will also help the organization unlock value from its growing data lake by identifying how consolidated data can improve product decisions, measure risk, evaluate results, track ROI, and support evidence-based prioritization across FX and cross-border initiatives.

Requirements

10 or more years of work experience with a Bachelor’s Degree or at least 8 years of work experience with an Advanced Degree (e.g. Masters/ MBA/JD/MD) or at least 3 years of work experience with a PhD
10–15 years of experience in product management or a related field.
Proven experience in product management, with significant leadership experience guiding product teams, influencing cross-functional stakeholders, and driving outcomes across complex organizations.
Strong ability to operate in complex, matrixed environments and influence outcomes across teams through collaboration, credibility, and structured problem-solving.
Deep understanding of product discovery, roadmap planning, requirements definition, agile delivery, stakeholder management, product operating models, and outcome-based measurement.
Experience translating ambiguous business, operational, or technical problems into clear use cases, platform capabilities, product requirements, success metrics, and execution plans.
Strong understanding of enterprise systems, APIs, web services, data flows, transaction processing, platform architecture, or large-scale financial technology environments.
Hands-on fluency with AI tools used for product management, strategy, analysis, communication, documentation, workflow automation, and organizational enablement.
Demonstrated ability to use AI in practical product workflows, including research synthesis, requirements creation, prioritization, roadmap planning, meeting summarization, documentation, data analysis, and executive storytelling.
Ability to create reusable AI prompts, workflows, templates, playbooks, demos, and education materials that help teams improve productivity, quality, and consistency.
Experience studying organizational workflows and identifying where AI can improve speed, clarity, decision-making, collaboration, and measurable business outcomes.
Experience working with data platforms, data lakes, analytics environments, dashboards, or business intelligence tools to support product and business decision-making.
Strong understanding of product metrics, business KPIs, operational metrics, risk indicators, and ROI measurement.
Ability to partner with data, analytics, finance, risk, compliance, architecture, and technology teams to define meaningful measurement frameworks and decision-support capabilities.
Excellent communication skills, with the ability to simplify complex topics, influence senior stakeholders, and educate teams through practical examples.
Strong analytical, organizational, and problem-solving skills.
Self-starter with a proactive approach to identifying opportunities, resolving challenges, and driving outcomes.
U.S. Applicants Only

Nice To Haves

12 or more years of work experience with a Bachelor’s Degree or 8-10 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 6+ years of work experience with a PhD

Responsibilities

Serve as a horizontal product leader across FX and Cross-Border Product and Platform Architecture, influencing outcomes through collaboration, structure, credibility, and product expertise.
Partner across product, platform architecture, engineering, data, analytics, operations, risk, compliance, finance, and business teams to align priorities, improve execution, and drive shared outcomes.
Translate complex FX and cross-border business needs into clear product opportunities, platform capabilities, use cases, requirements, success metrics, and roadmap recommendations.
Act as a hands-on AI product enablement leader, helping teams adopt AI through practical demos, working sessions, templates, prompt libraries, playbooks, and repeatable workflows.
Apply AI tools directly to improve product discovery, stakeholder synthesis, requirements drafting, user story creation, roadmap planning, prioritization, executive communication, documentation, meeting follow-up, risk identification, and knowledge management.
Study how teams work today and identify where AI can reduce manual effort, improve quality, accelerate decision-making, strengthen communication, and create measurable productivity gains.
Help define how the organization’s data lake can be used to improve decisioning, including measurement of product performance, operational outcomes, risk indicators, adoption, business results, and ROI.
Partner with data and analytics teams to define dashboards, scorecards, KPIs, leading and lagging indicators, and executive reporting views.
Use AI and analytics to surface trends, anomalies, risks, opportunities, and performance drivers from structured and unstructured data.
Support roadmap prioritization and investment decisions by helping teams evaluate value, risk, cost, effort, timing, dependencies, and strategic impact.
Promote responsible AI and data usage aligned with privacy, security, compliance, data governance, human review, and accuracy validation expectations.
Improve product operating practices across teams, including product briefs, decision records, use cases, user stories, acceptance criteria, roadmap narratives, and outcome-based measurement.
Drive clarity in ambiguous situations by framing problems, identifying tradeoffs, surfacing dependencies, and helping stakeholders reach decisions.