SW Engineer

Visa's Technology Organization

Visa’s Technology Organization is a community of problem solvers and innovators reshaping the future of commerce. We operate the world’s most sophisticated processing networks capable of handling more than 65k secure transactions a second across 80M merchants, 15k Financial Institutions, and billions of everyday people. While working with us you’ll get to work on complex distributed systems and solve massive scale problems centered on new payment flows, business and data solutions, cyber security, and B2C platforms.

We are looking for Versatile, curious, and energetic Software Engineers who embrace solving complex challenges on a global scale. As a Visa Software Engineer, you will be an integral part of a multi-functional development team inventing, designing, building, and testing software products that reach a truly global customer base. While building components of powerful payment technology, you will get to see your efforts shaping the digital future of monetary transactions.

• Design and develop systems that touch 40% of the world’s population while influencing Visa’s internal engineering standards for scalability, security, reusability, and automation.
• Collaborate cross‑functionally to create design artifacts and deliver best‑in‑class software solutions across Visa’s technical portfolio.
• Leverage AI/ML technologies—including model‑driven decisioning, anomaly detection, predictive analytics, and intelligent automation—to enhance product functionality and operational effectiveness.
• Contribute to advancements in Payment Services, Real‑Time Payments, Fraud & Risk Systems, Transaction Platforms, and Buy Now Pay Later technology using both software engineering expertise and data‑driven approaches.
• Develop robust and scalable products for merchants, B2B partners, and government solutions.
• Participate in global and local initiatives, mentoring engineers and exploring new technologies, including ML frameworks, data platforms, and generative AI tools.

• Demonstrates relevant technical working knowledge to understand requirements.
• Partner with product owners to gather and refine business and technical requirements, including identifying opportunities for AI/ML integration.
• Develop advanced, scalable architecture solutions that incorporate ML‑powered components (e.g., scoring engines, real‑time inference, intelligent routing).
• Provide domain expertise for technical documentation, including algorithmic approaches and data‑driven solution designs.
• Play a key role in delivering new features end‑to‑end across products, including ML‑enhanced functionality, data pipelines, and intelligent services.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

• 5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.

• Java expert with experience building and consuming REST APIs and backend technologies including J2EE, JDBC, JMS, Spring, Spring Boot, Spring Batch, Python and Vertex.
• Proficiency in front‑end web development technologies like React
  
  JS/Angular/NodeJS.
• Experience with Kafka, Redis, or No
  
  SQL data stores.
• Hands‑on experience with MySQL, DB2, Oracle, and strong SQL proficiency.
• Deep understanding of OOP concepts and design patterns.
• Experience with Agile development, CI/CD, GIT, Git Hub Actions, Maven, Jenkins, Chef, Sonar, and Junit.
• Practical experience integrating AI/ML capabilities into production systems (e.g., fraud detection, anomaly detection, scoring, recommendations, intelligent routing).
• Familiarity with ML frameworks:
  Tensor Flow, PyTorch or equivalent.
• Experience building Generative AI applications, conversational AI, RAG, consuming ML services, inference APIs, MCP servers and MCP Hub.
• Understanding of feature engineering, model lifecycle management, ML‑Ops, and data pipeline design.
• Experience with large‑scale data processing technologies supporting ML workloads.
• Exposure to…