Staff Software Engineer

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

The Staff Software Engineer would be a part of a high-performance global team responsible for the delivery of features in the Resolve Online program.

We are seeking a Staff Software Engineer to join the Visa Resolve Online (VROL) Engineering team. You will contribute to the development of next-generation AI solutions that transform dispute management through Generative AI, Machine Learning, Conversational AI, Intelligent Document Processing, and Developer Productivity tools.

This role is ideal for engineers who are passionate about AI technologies and eager to work on enterprise-scale solutions that directly impact customer experience and operational efficiency. Every engineer in this team will work in close collaboration with Generative AI tools as development companions, leveraging Visa’s extensive portfolio of AI models, tools, and experimentation platforms.

As a key member of the delivery execution team, candidates would need to create scalable designs, write maintainable code, reusable components/services/utilities, and test cases.

The successful candidate will become a recognized Subject Matter Expert, responsible for contributing to the development and implementation of dispute processing capabilities for Visa Resolve Online application.

Responsibilities:

• Works independently on defined problems and features
• Applies established architectural patterns with good technical judgment
• Takes ownership of code quality, testing, and production reliability
• Design, build, and ship AI-powered tools that enhance the autonomous development lifecycle - from code commit to production deployment
• Convert AI concepts into concrete, working products with clear success metrics and measurable impact
• Build AI systems that improve software quality through intelligent code analysis, test optimization, and automated defect detection
• Create AI-driven solutions that provide deep insights into code quality, technical debt, and system performance
• You are expected to deliver consistently, contribute to improving the codebase and systems you work on, and operate with a production‑first mindset.
• Design and implement small to medium‑sized features or components based on defined requirements and reference architectures.
• Apply approved architectural patterns (e.g., microservices, event‑driven messaging, APIs) correctly and consistently.
• Translate functional requirements into clean, efficient, and maintainable code.
• Translating real-world business challenges into measurable machine learning metrics
• Explain complex algorithmic decisions and model predictions to non-technical stakeholders
• Contribute to design discussions and document implementation decisions where appropriate.
• Write high‑quality, readable, and testable code aligned with defined engineering standards.
• Develop and maintain automated unit and component tests.
• Identify and address defects, performance issues, and reliability gaps in owned areas.
• Participate in production releases and operational readiness activities.
• Drive continuous innovation in AI-driven development through research, prototype building, and production rollouts.vWork closely with Product Managers, DevOps, and peer engineers.
• Mentor junior engineers and contribute to best practices for building AI enabled applications.

Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications:

• 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.

Preferred Qualifications:

• 6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD in Computer Science, Software Engineering, Artificial Intelligence, or related technical field
• Strong background in AI systems with proven ability to design, build, and ship AI-powered solutions that enhance the autonomous development lifecycle, improve software quality.
• Experience with Python and Machine Learning fundamentals, including preparing and analyzing data, building and evaluating predictive models, and improving model performance. Familiarity with common Machine Learning techniques such as regression, decision trees, random forests, and ensemble methods is beneficial. Experience using tools such as Python, scikit-learn, pandas, NumPy, and Jupyter notebooks is preferred. An understanding of model evaluation concepts (e.g., accuracy, precision, recall, and related metrics) is helpful, but deep expertise in all areas is not required.
• 5–8 years of hands-on software engineering experience building, delivering, and supporting enterprise-grade Java/J2EE applications, preferably using Spring Boot, RESTful APIs, microservices, and modern front-end frameworks such as Angular or React.
• Strong foundation in software engineering principles, clean code practices, object-oriented design, data structures, algorithms, distributed systems, and scalable application architecture.
• Hands-on experience with AI-assisted software delivery, including effective use of generative AI coding assistants and developer tools such as Claude Code CLI, GitHub Copilot, Cline, prompt engineering, AI-supported code review, test generation, documentation, and productivity workflows.
• Ability to validate, refactor, and secure AI-generated code with strong human oversight, ensuring correctness, maintainability, performance, compliance, and production reliability.
• Working knowledge of applied AI concepts relevant to software engineering, such as large language models, embeddings, retrieval-augmented generation, agentic workflows, model limitations, data privacy, and responsible AI practices.
• Knowledge of Agentic Skills, including setting up, reviewing, and maintaining skills, knowledge graphs, and related AI orchestration patterns to support reliable, context-aware developer productivity workflows.
• Proven ability to design and deliver production-ready services using APIs, event-driven messaging, caching, resiliency patterns, observability, and secure integration practices.
• Solid experience with relational databases and SQL; experience with DB2, MySQL, performance tuning, schema design, and data access optimization is preferred.
• Experience with cloud-native engineering practices and container platforms such as Docker, Kubernetes, or OpenShift, including deployment, monitoring, scaling, and operational readiness.
• Strong DevSecOps mindset with practical understanding of secure coding, vulnerability remediation, secrets management, dependency governance, logging, monitoring, and incident response.
• Experience working in Agile delivery teams with strong ownership of stories, design decisions, engineering quality, production support, and continuous improvement.
• Strong analytical, problem-solving, and debugging skills with the ability to troubleshoot complex issues across application, integration, data, infrastructure, and AI-assisted delivery workflows.

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