Staff Software Engineer

About Visa

Visa stands as a global leader in payment technologies, enabling seamless transactions among consumers, merchants, financial institutions, and governments across over 200 countries worldwide. The company is committed to delivering the most efficient payment and receipt solutions to uplift everyone, everywhere.

Joining Visa offers the opportunity to make a meaningful impact on a large scale by addressing challenging problems, advancing your skills, and influencing lives across the globe.

Role Overview

As a Staff Software Engineer on the Visa Resolve Online (VROL) team, you will engage with a high-performing global group focused on delivering innovative features. This role emphasizes the development and implementation of AI-driven technologies including Generative AI, Machine Learning, Conversational AI, Intelligent Document Processing, and developer productivity tools to revolutionize dispute management systems.

This position suits engineers passionate about artificial intelligence who want to work on enterprise-scale solutions affecting customer experiences and improving operational processes. Collaboration with generative AI development tools and Visa’s extensive AI resource portfolio is integral to this role.

Responsibilities

• Work autonomously to solve defined problems and develop software features.
• Employ sound architectural design patterns with prudent technical judgment.
• Ensure excellence in code quality, testing, and system reliability in production environments.
• Design and deliver AI-powered tools that enhance the autonomous software development lifecycle, from code commitment through to production deployment.
• Transform AI concepts into concrete, measurable products that demonstrate clear impact.
• Develop intelligent AI systems that augment software quality through code analysis, testing optimization, and automated defect identification.
• Create solutions providing insights into code quality, technical debt, and system performance.
• Maintain a consistent delivery cadence, improve systems and codebases, and adhere to a production-first mindset.
• Design and implement features or components of small to moderate size based on requirements and predefined architectures.
• Apply standard architecture patterns such as microservices, event-driven messaging, and APIs appropriately and effectively.
• Translate business challenges into measurable machine learning objectives.
• Communicate complex algorithmic processes and model outputs clearly to non-technical team members.
• Participate in design discussions and document decisions.
• Produce clean, readable, high-quality, and well-tested code that aligns with engineering standards.
• Develop and maintain automated unit and component testing suites.
• Identify and resolve bugs, performance bottlenecks, and reliability issues within assigned domains.
• Support production deployments and ensure operational readiness.
• Drive AI-driven innovation through continuous research, prototyping, and production integration.
• Collaborate closely with Product Managers, DevOps teams, and fellow engineers.
• Mentor junior engineers and promote best practices for AI-enabled software development.
• Comply with Visa's hybrid working model requiring at least three days onsite per week as coordinated with management.

Qualifications

Minimum Requirements:

• At least 5 years of relevant professional experience with a Bachelor's degree, or 2 years with an advanced degree (e.g., Master's, MBA, JD, MD), or no experience with a PhD; alternatively, 8 or more years of relevant work experience.

Preferred Qualifications:

• 6+ years experience with a Bachelor's degree or 4+ years with an advanced degree or up to 3 years with a PhD in Computer Science, Software Engineering, AI, or related fields.
• Proven experience in AI systems design and delivery, building solutions that enhance autonomous development lifecycles and boost software quality.
• Proficiency in Python and foundational Machine Learning concepts including data preparation, predictive modeling, evaluation metrics, with familiarity in common ML techniques (regression, decision trees, random forests, ensembles) and tools such as scikit-learn, pandas, NumPy, and Jupyter notebooks.
• 5 to 8 years of hands-on software engineering experience developing and maintaining enterprise-grade Java/J2EE applications, ideally with Spring Boot, RESTful APIs, microservices, and front-end frameworks like Angular or React.
• Strong grounding in software engineering principles including object-oriented design, data structures, algorithms, distributed systems, and scalable application architectures.
• Experience utilizing AI-assisted delivery tools, including generative AI coding assistants like Claude Code CLI and GitHub Copilot, with competencies in prompt engineering, AI-aided code review, test generation, documentation, and productivity enhancements.
• Skill in validating, refactoring, and securing AI-generated code with human oversight to ensure correctness, maintainability, compliance, and reliability.
• Knowledge of applied AI concepts for software engineering such as large language models, embeddings, retrieval-augmented generation, agentic workflows, data privacy, and responsible AI practices.
• Understanding of Agentic Skills and AI orchestration for context-aware development workflows supporting productivity.
• Demonstrated ability to design and implement production-grade services using APIs, event-driven systems, caching, resiliency, observability, and secure integration approaches.
• Experience with relational databases and SQL, including DB2, MySQL, performance tuning, schema design, and data access optimization.
• Familiarity with cloud-native engineering and container technologies such as Docker, Kubernetes, OpenShift, with abilities in deployment, monitoring, scaling, and operational readiness.
• DevSecOps awareness with expertise in secure coding practices, vulnerability mitigation, secrets management, dependency control, logging, monitoring, and incident management.
• Experience in Agile environments demonstrating ownership over tasks, design, engineering quality, and production support.
• Strong analytical, problem-solving, and debugging skills to address complex issues spanning application, integration, data, infrastructure, and AI-assisted workflows.
• Excellent communication capabilities for articulating technical decisions and collaborating across product, architecture, DevOps, QA, and security teams with clear documentation.
• Experience in financial services, payments, dispute processing, or mission-critical enterprise platforms is highly advantageous.

Work Location Policy

Visa requires at least three days per week working onsite in Singapore, with specifics coordinated by your hiring manager.

Visa Equal Opportunity Employer Statement

Visa provides equal employment opportunities without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability status, or protected veteran status. Visa also considers applicants with criminal records in accordance with applicable laws and EEOC guidelines.