As a Lead Software Engineer, you will be an integral part of a multi-functional development team inventing, designing, building, and testing products that reach a truly global customer base.
- You will face big challenges and question the status quo, changing the way data products are developed at Visa! Come join us and see your efforts shape the digital future of payments.
- The focus is on defining, executing, and delivering product and technical features at scale quickly and promoting a diverse culture of cross-functional collaboration and engineering excellence. Be an idea leader and bring industry best practices to benefit the team and the wider organization. The ability to balance demanding business capabilities with building for operational excellence while meeting regulatory, security and privacy requirements.
- Ability to quickly grasp and evaluate new ideas and technologies from internal and external sources. Lead/Influence multiple teams, matching them with appropriate technology and business problems while building a culture of both innovation and drive for excellence.
- Transform our digital offerings by leveraging AI to enhance our current product line and develop exciting new products targeting our banking, fintech and integration partners, which will enable the next wave of innovation in payments. We need a strong technology leader, who is an expert in data science, agile delivery, building purpose driven teams, and has a background in complex integration projects. Prior experience in payments, or a background in building high volume transaction and data processing systems is preferred.
- The successful candidate will be comfortable navigating the challenging dynamic payments space and leading global teams responsible for platform transformation efforts. This candidate will play a pivotal role in our continued embrace of AI, seeking new paths to revenue by improving delivery efficiency and pushing forward for new products.
Essential Functions:
- Design, build, and ship AI-powered features and tools
- Convert AI concepts into concrete, working products with clear success metrics and measurable impact
- Build AI systems and ML models for problems such as Search, AI Assistants, predictive insights and analytics
- Provides technical expertise and mentors others to implement extensible, maintainable, and reusable code, defines framework, principles, coding patterns, guidelines, styles, and standard methodologies, and adheres to all security requirements for the application of artificial intelligence and data science.
- Ensures adherence to data management principles, governance, process, and tools to maintain data quality across products.
- Advises on technical specifications during discussions with collaborators (e.g., Product owners, business partners, Cybersecurity) to identify and clarify sophisticated technical or business requirements and identify business needs and upstream and/or downstream system/application dependencies.
- Defines technical standards for the design and documents the architecture for a complex product, using existing architecture design patterns.
- Oversees and establishes unit testing requirements of unit testing to confirm functional capability of code, acts as subject matter expert in testing for coding standards and security scans, strategically leads user acceptance testing in collaboration with customer across multiple domains.
Basic Qualifications
- 15 or more years of work experience with a Bachelor s Degree in computer science or with an Advanced Degree.
- At least 8+ years experience in Distributed Systems / Software Development using Java, Python, Go or any other programming language.
- GenAI experience, building models for solving complex problems in Search, AI Assistants, Predictive Insights.
- Strong understanding of GenAI technologies and experience building a product using any LLM.
- Experience with CI/CD pipelines, using tools such as GIT, Maven, Jenkins, Chef, Sonar, JUnit.
- Experience with Agile and Test Driven Development methodology.
- Three (3) years of experience building and pushing code into production.
- Experience with model building
- SDLC: Strong understanding of the entire software development lifecycle, including testing strategies, automation, deployment, and release strategies.
- Observability: Deep expertise in observability, including monitoring, logging, and alerting.
- GAI: utilization of Generative AI models and software for code development
- Knowledge of data structures, which consist of data organization, management, and storage formats that enable efficient access and modifications. This includes a collection of data values, the relationships among them, and the functions or operations that can be applied to the data.
