Product Analyst - Generative AI Platform

Visa•Austin, TX

3h•Hybrid

About The Position

The Generative AI Platform Product team is building a scalable, next-generation platform that enables teams across the organization to develop, deploy, and govern generative AI-powered products. The team partners across engineering, product, data science, and all the business functions to deliver secure, reliable, and reusable generative AI capabilities that accelerate innovation and drive business value. Visa is seeking a Product Analyst to help define, build, and scale our next-generation generative AI capabilities across the organization. This role sits at the intersection of product, data, and engineering and is ideal for someone with strong analytical skills, product instincts, and a passion for generative AI. You will focus on requirements definition, analysis, execution support, and platform adoption, while gaining hands‑on exposure to how large‑scale generative AI platforms are built, governed, and scaled across a global organization.

Requirements

2 or more years of relevant work experience with a Bachelor’s Degree or at least 1 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD)

Nice To Haves

3 or more years of work experience and a Bachelors Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) 2+ years of experience in business or technical product management with strong generative AI or AI/ML, Data Science background Hands-on experience with prototyping, developing, and delivering generative AI solutions using APIs and simple code (e.g., Python), with the ability to build proofs of concept and demo technical platform capabilities.
Strong technical acumen and experience in AI platforms, AI/ML, Large Language Models (LLMs), evals and agentic systems.
Strong experience experimenting with generative AI tools and APIs (e.g., OpenAI, Anthropic, etc.) for prototypes, analyses, or side projects.
Experience in product management, with demonstrated ability to launch and manage new product releases being part of a matrixed organization in a highly technical Strong technical acumen on AI platforms, AI/ML, models, public cloud deployments with the ability to build Proof of concepts and demo technical platform capabilities.
Understand of technical concept of data processing at scale on prem and cloud.
Experience in and/or significant exposure to the payments industry specifically within new applications for Artificial Intelligence and Machine Learning.
Proficiency with software development methodologies such as Agile and experience working with Scrum teams and matrixed organizations.

Responsibilities

Define the product roadmap and execution for generative AI platform and AI-powered experiences.
Translate customer and stakeholder problems into clear product requirements, epics, and acceptance criteria for generative AI features and workflows.
Analyze user behavior, product metrics, and LLM model performance to provide actionable insights, inform prioritization, and measure feature impact.
Support prioritization of the product backlog using data, customer feedback, and business impact, ensuring a balance between quick wins and strategic bets.
Conduct market and competitive research on generative AI tools, LLMs, and vendors to inform build vs. buy decisions and identify new opportunities.
Collaborate closely with engineering and business partners to scope experiments, define MVPs, and guide features from ideation through launch.
Help baseline product performance, define OKRs/KPIs for generative AI features, and track progress over time.
Contribute to documentation (requirements, release notes, FAQs, run-books) to support stakeholders and enable smooth adoption of the generative AI platform.
Partner with risk, security, and legal teams to ensure responsible AI, governance, and compliance requirements are embedded into product design.
Support enablement efforts by helping create demos, training materials, and best-practice guides that drive AI literacy and adoption across the organization.