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
Common Purpose, Uncommon Opportunity. Everyone at Visa works with one goal in mind – making sure that Visa is the best way to pay and be paid, for everyone everywhere. This is our global vision and the common purpose that unites the entire Visa team. As a global payments technology company, tech is at the heart of what we do.
We are also global advocates for financial inclusion, working with partners around the world to help those who lack access to financial services join the global economy. Visa’s sponsorships, including the Olympics and FIFA™ World Cup, celebrate teamwork, diversity, and excellence throughout the world. If you have a passion to make a difference in the lives of people around the world, Visa offers an uncommon opportunity to build a strong, thriving career. Visa is fueled by our team of talented employees who continuously raise the bar on delivering the convenience and security of digital currency to people all over the world. Join our team and find out how Visa is everywhere you want to be.
The Data and Artificial Intelligence Platform (DAP) group is a key component of Visa's Technology organization that provides the enabling technology and processes to handle Visa's data assets and deliver valuable information, products, and services to customers. DAP delivers secure, high-quality and easy-to-use Visa core data assets as a service, together with reliable and scalable data platform as a service, to enable Visa and our partners to rapidly and efficiently innovate data-driven business products and services to lead the digital payment industry. Areas of focus include Business Intelligence and Analytics, Artificial Intelligence, Machine Learning, Data as a Service, and Platform as a Service etc. The portfolio comprises of over 60 data products & platforms for various external clients and internal lines of business. We provide services on behalf of traditional bank customers to millions of cardholders and merchants globally. Our application development is on the cutting edge of technology, and we are viewed as innovative leaders within our industry.
The Platform operationalizes the delivery of AI and decision intelligence to ensure ongoing business values. Built with composable AI capabilities, privacy-enhancing computation, and cloud native platforms, platform automates the updates to data, models, and applications. If you want to be in the exciting payment and AI space, learn fast, and make big impacts, this is an ideal place for you!
We are responsible for designing, developing, and implementing next generation data platforms to drive incremental revenue.
Key Responsibilities:
Generative AI & Innovation
- Lead the design, development, and deployment of GenAI solutions, including LLM integration, prompt engineering, RAG systems, and domain‑specific model customization.
- Evaluate emerging AI capabilities and prototype innovative solutions to accelerate business transformation.
- Drive experimentation frameworks that validate model performance, user experience impact, and production feasibility.
Analytical & Data‑Driven Applications
- Architect and build data‑intensive analytical applications that enable real‑time insights, predictive intelligence, and automated decisioning.
- Partner with data engineering teams to design scalable data pipelines, metadata systems, and high‑quality feature stores.
- Ensure analytical systems meet enterprise requirements for accuracy, governance, and performance.
Enterprise-Scale Engineering
- Architect cloud‑native applications capable of handling large-scale, high‑availability workloads.
- Oversee performance optimization, distributed processing, caching strategies, and operational monitoring.
- Ensure secure, compliant, and resilient engineering practices aligned with enterprise standards.
Microservices Architecture
- Design and evolve microservices architectures using best practices such as domain-driven design, event-driven patterns, and API-first development.
- Implement robust inter‑service communication (REST, gRPC, messaging) and reliability patterns (circuit breakers, rate limiting).
- Guide engineers on scaling, testing, and maintaining distributed services.
Leadership & Collaboration
- Mentor engineering and data science teams in modern AI, GenAI adoption, and architectural excellence.
- Translate business goals into actionable engineering roadmaps and AI solution blueprints.
- Define coding standards, architecture guidelines, model governance, and delivery best practices.
- Collaborate closely with product, security, and platform teams to align AI solutions with enterprise strategy
This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.
Qualifications
Basic Qualifications: 10+ years of relevant work experience with a Bachelor’s Degree or at least 7 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 4 years of work experience with a PhD, OR 13+ years of relevant work experience. Preferred Qualifications: 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 12–14 years of software engineering experience, including significant leadership in AI/ML and GenAI initiatives. Expertise in LLMs, embeddings, RAG systems, model fine tuning, and GenAI frameworks (LangChain, LlamaIndex, Hugging Face, etc.). Strong proficiency in Python plus enterprise languages (Java/Scala/Go). Experience building scalable cloud-native systems (AWS, Azure, GCP) and microservices architectures. Hands-on experience with Kubernetes, Docker, CI/CD pipelines, and observability tools. Deep understanding of MLOps practices, model lifecycle management, and production AI monitoring. Proven ability to deliver large-scale analytical applications and distributed data workflows. Strong leadership, communication, and cross-functional collaboration skills.
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 protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.