Senior Product Manager

Visa•Austin, TX

12d•$152,200 - $243,700•Hybrid

About The Position

Visa's AI/ML Platforms team builds the next-generation, scalable, and responsible AI/ML infrastructure and services that power Visa's most critical capabilities. The platforms our team delivers prevent fraud, enable new revenue streams, and safeguard billions of transactions every day. We are seeking a Senior Manager, Product Management to own the roadmap and delivery of our core AI/ML platform services and to lead the planning and execution of migrating these workloads to a modern, cloud-native foundation — the backbone that every AI/ML team at Visa builds on. This is an individual contributor role reporting to the Director of Product Management, AI/ML Products. You will lead complex, cross-functional workstreams and platform initiatives through influence, deep technical fluency, and disciplined product execution. You will own and execute against the AI/ML platform product roadmap, translating product direction into well-scoped capabilities, requirements, and outcomes that engineering and data science teams can build against clarity and speed. You will own the discovery, definition, and delivery of platform capabilities end to end. This is an exciting opportunity to run and scale AIML platform: own the delivery, reliability, performance, and cost-efficiency of the AI/ML platform services — model training and experimentation environments, inference, and the data and tooling pipelines — that the whole company depend on. Second, contribute to the cloud transformation journey: drive the planning and hands-on execution of transforming these AI/ML workloads to cloud-native architecture, partnering closely with engineering and architecture to modernize how the platform scales. You will also partner on the platform's readiness for emerging Generative AI workloads, contributing to capability definition as the team's GenAI investments grow. Success in this role requires deep collaboration across a highly matrixed organization. You will work shoulder-to-shoulder with platform engineering, ML engineering, data science, architecture, security, risk, legal, and compliance partners to align priorities, sequence delivery, and remove ambiguity. The ideal candidate is a hands-on platform product manager who is equally comfortable in a technical design discussion about cloud-native architecture, inference at scale, Kubernetes, and platform reliability as they are framing trade-offs for senior leaders, writing crisp requirements, and driving an Agile delivery cadence — all while balancing speed, scalability, cost, governance, and the regulatory and data-privacy obligations inherent to payments and financial services. You bring strong judgment, a bias for execution, and the ability to make progress amid ambiguity in a fast-moving domain.

Requirements

8 or more years of relevant work experience with a bachelor's 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
9 or more years of relevant work experience with a bachelor's 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
Bachelor's or advanced degree in Computer Science, Engineering, Data Science, or related technical field.
Demonstrated experience as a platform or technical product manager delivering AI/ML, data, or developer-platform/infrastructure capabilities as an individual contributor, leading cross-functional workstreams.
Hands-on experience planning and executing the transformation of AI/ML, data, or large-scale application workloads to cloud-native architectures on AWS, Databricks — with a strong grasp of scalability, elasticity, reliability, and cloud cost optimization.
Proven ownership of AI/ ML production platform management— SLAs, observability, capacity planning, and lifecycle management — for systems that internal teams depend on.
Strong working knowledge of Cloud and MLOps frameworks, CI/CD for ML, and containerization and orchestration, along with model governance and lifecycle management.
Practical understanding of responsible AI principles and how governance, evaluation, and data privacy are operationalized in a platform.
Familiarity with the payments, fraud, risk, or broader financial services domain, including the regulatory compliance and data privacy considerations that shape AI/ML platforms.
Proven ability to influence and partner across a highly matrixed organization, aligning business, product, and technology stakeholders without formal authority.
Excellent written and verbal communication skills, with the ability to translate complex technical concepts into clear trade-offs and decisions for both engineers and senior leaders.
Proficiency with Agile delivery and tooling such as JIRA, Claude Code, Codex, and a track record of maintaining a healthy, well-prioritized backlog.
Experience in identifying, assessing, and managing tradeoffs in product development, build vs buy tech decisions.

Nice To Haves

People-management or team-leadership experience is a plus, though this is an individual contributor role and direct management is not required.
Exposure and hands-on development to Generative AI platform concepts (model serving, inference, gateways, RAG/vector infrastructure, guardrails) and enthusiasm to grow into them; deep GenAI ownership is welcome

Responsibilities

Drive conceptualization, prototyping, and launch of AI-powered solutions at the intersection of payments and technology
Build business cases for new AI/ML capabilities and continuously evolve platform features to meet practioner needs
Partner with business units, product, and Eng teams to ensure alignment and flawless execution
Monitor market trends, competitive dynamics, and clients' needs to guide platform evolution and long-term planning.
Advocate for exceptional customer experiences powered by advanced AI capabilities
Define detailed platform requirements, acceptance criteria, and success metrics (e.g., SLAs, operational KPIs).
Apply Hands-on expertise in designing cloud-native AIML solutions and enterprise-scale applications on the cloud.
Lead backlog grooming and facilitate collaboration across product, Eng and data science teams
Ensure platform capabilities meet compliance, model risk management, and onboarding requirements.
Ensure development and delivery adherence to timelines, quality standards, and strategic objectives.
All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Claude Code, Co-pilot) to support everyday work.