Sr. SW Engineer (Full Stack)

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. Visa will accept applications for this role until at least 11-30-2026 Job Description Software Development Engineers are expert problem-solvers and builders who design, implement, and improve software applications and systems. In this role, engineers spend approximately 80–90% of their time coding, working hands-on with code, data, and modern tools (including AI-assisted development, cloud services, and automation frameworks) to deliver secure, scalable, and high-quality technology solutions that drive business outcomes in the fintech sector. They collaborate with cross-functional teams – product managers, designers, data scientists, QA, operations, and compliance – to translate business requirements into robust technical solutions, all while adhering to best practices, security standards, and regulatory requirements. All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work. Key Responsibilities - Design, develop, and maintain full stack features across React/JavaScript/TypeScript front ends and Java/Spring Boot and Node.js back-end services, owning delivery from requirement through production. - Build and ship production solutions using agentic AI — LLM-backed services, tool-calling and multi-step agents, MCP servers and clients, retrieval-augmented generation pipelines, prompt and context engineering, evaluation harnesses, and guardrails for safety, cost, and latency. - Apply AI-assisted engineering tools across the development lifecycle — code generation, refactoring, test authoring, code review, debugging, and documentation — and help the team raise its baseline productivity and quality through better AI workflows. - Collaborate with stakeholders to interpret requirements for project components and incorporate feedback into future designs or solution fixes. - Translate business requirements by verifying assumptions and escalating potential design issues to appropriate stakeholders. - Participate in system design and architecture for platform components and AI-enabled services, refining code plans and contributing to design documentation. - Design, build, and consume secure, well-documented REST APIs and microservices used by internal teams and external developer clients. - Contribute to project estimation and escalate issues that may cause delays. - Develop, implement, and maintain code for products, services, or components, applying coding patterns, guidelines, and best practices. - Apply debugging and observability tools to verify assumptions and proactively flag issues before they occur. - Participate in code reviews to ensure coding standards are followed and address routine pull requests. - Create test plans and configure testing procedures — including unit, integration, automation, and evaluation testing for AI-driven features — to identify and resolve defects for multiple features. - Respond to support requests during on-call rotations, troubleshooting issues and deploying fixes. - Leverage and build knowledge of software developer tools to create, debug, and maintain code for components. - Mentor junior engineers, promote engineering best practices, and help the team adopt AI-first engineering patterns responsibly. - Remain current in skills by investing time in training resources to improve product availability, reliability, efficiency, observability, and performance. Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications - 2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience - Hands-on professional experience building full stack applications with Java and JavaScript. - Hands-on experience with React, Spring Boot, Node.js, relational databases (e.g. MySQL, Postgres), and Linux. - Demonstrated hands-on experience building and shipping solutions using agentic AI — including LLM APIs, tool/function calling, agent frameworks, or MCP-based integrations — with examples you can walk through in detail. - Experience designing, building, and testing enterprise-scale web services and REST APIs. - Ability to work effectively across Development, Quality Assurance (QA), automation testing, and production support functions, adapting to evolving project and business needs. Preferred Qualifications - 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) - Experience in technologies/software systems or a directly related field (minimum four years). - Experience developing and/or implementing web-based or mobile applications (minimum three years). - Depth in modern front-end engineering — React with TypeScript, state management, component design systems, performance optimization, and accessibility. - Depth in back-end engineering — Spring Boot microservices, Spring Security, JPA/Hibernate, asynchronous and event-driven patterns, caching, and API versioning. - Production experience with agentic AI patterns — multi-step and multi-agent orchestration, tool and MCP server design, retrieval-augmented generation, vector stores and embeddings, prompt and context engineering, structured output, streaming responses, evaluation and regression testing of AI behavior, observability and tracing for AI workloads, and controls for cost, latency, hallucination, and prompt injection. - Demonstrated experience leveraging Generative AI and AI-assisted engineering tools to improve development velocity, code quality, testing effectiveness, and engineering productivity. - Experience with microservices, Kubernetes, Docker, and cloud-native architectures. - Experience working in CI/CD environments and related tooling. - Experience in system design and architecture for product components. - Experience in debugging and troubleshooting software issues. - Experience in code review and applying coding standards. - Experience in test planning and execution for software features, including test automation. - Experience in responding to support requests and deploying fixes. - Experience in using software developer tools for code creation and maintenance. - Experience working on client-facing or developer-facing platforms, APIs, or technical teams (minimum two years). - Experience with API security and developer platform concerns — OAuth 2.0, OIDC, mutual TLS, API keys, token lifecycle, rate limiting, and secure secret handling. - Experience in integrating feedback into design and solution fixes. - Experience in mentoring junior engineers and collaborating with cross-functional teams. - Experience applying Agile software development practices. - Ability to contribute across application development, quality engineering, test automation, release validation, and production support functions. - Strong interpersonal, collaboration, and facilitation skills. - Ability to communicate technical and business concepts effectively to technical and non-technical stakeholders. - Adaptability and enthusiasm for learning new technologies, particularly in a fast-moving AI landscape. - Ability to create technical design, implementation, and operational documentation. - Experience designing and developing scalable, highly available systems. - Strong problem determination and ro