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About Us
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.
At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.
Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.
Job Description
The Governance Platforms team is building the next generation of AI governance products and capabilities that enable Visa to innovate faster while operating safely, responsibly, and at enterprise scale. Our mission is to transform complex governance, risk, cyber, privacy, and regulatory requirements into intuitive platform experiences that are embedded directly into how AI and data products are built, approved, monitored, and operated. By connecting governance, technology, and product management, we create the trust layer that allows AI innovation to accelerate.
About the role:
This is not a traditional governance role. The primary responsibility is product management, including vision, roadmap development, requirements definition, stakeholder alignment, prioritization, user experience design, adoption, and measurable business outcomes. Governance domain knowledge is important, but product leadership is essential.
The senior product manager will build and scale Visa's next generation AI Governance Platform capabilities. This role is responsible for defining and delivering products that enable governance, risk management, oversight, certification, and policy enforcement across the AI lifecycle. The ideal candidate is a strong product leader who excels at turning complex business challenges into intuitive products, measurable outcomes, and scalable platform capabilities.
The successful candidate will own strategic product initiatives spanning AI governance automation, cyber rules and policy translation into product requirements, intelligent risk and control scoring, audit remediation, and a scalable certification experience that turns governance evidence into clear deployment, remediation, recertification, and lifecycle decisions for AI assets.
Core Responsibilities
Product Strategy & Roadmap
- + Define product vision, strategy, and roadmap for governance platform capabilities. + Translate complex governance, cyber, risk, policy, and audit requirements into scalable platform solutions. + Prioritize features and investments based on business value, user needs, risk reduction, and operational impact. + Partner closely with Engineering, Architecture, UX, Data Science, and Governance stakeholders. + Lead UAT, release readiness, adoption planning, and product rollout activities. + Develop quarterly and multi-year product roadmaps.
AI Governance & Certification
- + Define and evolve governance certification capabilities across the AI lifecycle. + Design risk-based scoring models that support certification, recertification, and governance decision-making. + Define certification workflows, governance status models, decision criteria, and approval frameworks. + Partner with Risk, Privacy, Policy, Security, and Product teams to establish trusted certification standards.
Build Policy Enforcement Tools and Systems
- + Partner with Cybersecurity teams to implement governance guardrails and policy enforcement capabilities. + Drive self-service governance experiences that reduce manual dependency on security teams. + Lead product initiatives supporting audit findings, remediations, control validation, and evidence management. + Build scalable workflows that simplify audit preparation and improve governance transparency. + Ensure products generate measurable evidence that supports internal and external oversight activities. + Drive remediation tracking, exception management, and reporting capabilities.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.Qualifications
Basic Qualifications:
8 or more years of relevant work experience with a Bachelor Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD
Preferred Qualifications:
9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD
8+ years of product management experience building enterprise software, platforms, workflow applications, or data products.
Demonstrated ownership of product strategy, roadmap, and delivery.
Strong experience translating ambiguous problem statements into clear product solutions.
Experience working with cross-functional technology teams.
Ability to understand technical architectures, APIs, integrations, workflows, and platform ecosystems.
Experience defining product requirements and success metrics.
Strong analytical thinking and problem-solving skills.
Comfortable working with data, dashboards, reporting, and operational metrics.
Ability to influence without authority across diverse teams.
Strong written and verbal communication skills.
Ability to simplify complex concepts for technical and non-technical audiences.
Nice to Have Qualifications:
- Experience with AI, machine learning, generative AI, agents, or AI governance programs.
- Experience working with AI inventory, model management, monitoring, certification, or governance platforms.
Information for US Applicants
For roles located in the US, the estimated salary range for this position is $180,600.00 to $ 289,300.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.Work Hours
Varies upon the needs of the department.
Travel Requirements
This position requires travel 5-10% of the time.
Mental/Physical Requirements
This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.
Visa is an EEO Employer
Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.
Salary Context
This $180K-$289K range is above the 75th percentile for AI Product Manager roles in our dataset (median: $194K across 123 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Visa, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills in Demand for This Role
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $220,200 based on 947 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($234K) sits 7% above the category median. Disclosed range: $180K to $289K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Visa AI Hiring
Visa has 14 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, AI Software Engineer, Data Scientist. Positions span San Francisco, CA, US, Foster City, CA, US, Ashburn, VA, US. Compensation range: $171K - $326K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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