About the role
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 Overview: We are looking for a highly motivated Software Engineer to join the Payment Fraud Disruption engineering team within Visa's Ecosystem and Operational Risk organization. This is an exciting opportunity to work at the intersection of Data Engineering, Distributed Systems, Artificial Intelligence, and Generative AI while building next-generation platforms that help protect the Visa network and drive intelligent risk decisions. As part of an AI-first engineering organization, you will develop large-scale data platforms, real-time streaming solutions, GenAI-powered applications, and agentic workflows that support fraud detection, investigation, risk intelligence, and operational excellence. The ideal candidate is a strong software engineer with hands-on experience in data-intensive systems and a passion for applying Generative AI technologies to solve complex business challenges at scale. The candidate should also bring a reliability-first mindset and an interest in building secure, resilient, observable, and production-ready systems. What You Will Do: Build and maintain scalable data pipelines, APIs, microservices, and distributed applications that power fraud intelligence and risk solutions. Develop real-time and batch data-processing applications using modern data engineering technologies. Build and integrate Generative AI capabilities such as intelligent search, summarization, copilots, Retrieval-Augmented Generation, and agent-based workflows. Design services for reliability and resiliency by applying patterns such as retries, timeouts, circuit breakers, idempotency, failure isolation, and graceful degradation. Implement monitoring, structured logging, distributed tracing, dashboards, and actionable alerts to improve system visibility and operational readiness. Define and monitor service-health indicators across availability, latency, throughput, error rates, data quality, and resource utilization. Develop automated unit, integration, performance, resiliency, and deployment-validation tests. Identify production risks, system bottlenecks, recurring failures, and performance issues, and contribute to sustainable corrective actions. Participate in production support, incident triage, root-cause analysis, and post-incident improvement activities. Create and maintain operational documentation, troubleshooting guides, alerts, and runbooks for supported services. Collaborate with Product, Data Science, Platform Engineering, Site Reliability Engineering, and Security teams to deliver secure, scalable, and reliable solutions. Leverage AI-assisted development tools to improve engineering productivity, software quality, testing, and delivery consistency. Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field. 6 months to 2 years of software engineering experience developing enterprise applications, data platforms, distributed systems, or cloud-native solutions. Strong programming skills in Java and/or Python. Experience building APIs, microservices, data pipelines, or distributed applications. Understanding of data structures, algorithms, object-oriented design, and software engineering fundamentals. Experience with automated testing, source control, code reviews, and CI/CD practices. Foundational understanding of application monitoring, structured logging, alerting, and production troubleshooting. Strong analytical, problem-solving, communication, and collaboration skills. Preferred Qualifications: Experience with Kafka, Spark, relational databases, data modeling, and batch or real-time data pipelines. Familiarity with LLM applications, RAG, vector databases, prompt engineering, and agentic AI frameworks. Experience with cloud platforms, Docker, Kubernetes, CI/CD, and DevOps practices. Understanding of monitoring, logging, tracing, alerting, and production troubleshooting. Familiarity with resiliency patterns such as retries, timeouts, circuit breakers, idempotency, and graceful degradation. Exposure to performance testing, capacity planning, incident management, and root-cause analysis. Experience in fraud, cybersecurity, financial services, or large-scale data platforms is a plus. 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.