American Express—Software Engineer III

Job description

Description: The Enterprise Technology Services organization partners with every part of the American Express business to power the company’s growth and innovation with trust and efficiency, and drive competitive differentiation with speed, by supporting the delivery and operations of technology capabilities, platforms, and services globally. Specifically, the team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for external customers and internal colleagues. It also encompasses product management for core enterprise platforms, as well as technology risk and information security; enterprise data governance and platforms; digital product and design; and enterprise AI platforms across American Express. American Express is looking for a hands-on Software Engineer III in the Risk Decision Technology (RDT) organization for the Authorization Modernization Program (AMP) team. The RDT team is responsible for cross-domain, configurable platforms to enable best-in-class risk management and American Express growth with strong governance. The AMP team is on a journey to modernize and build next-gen authorizations platform. This role of Engineer will be an integral part of a team that designs and builds large-scale, high-transaction, cloud- native applications and drive us closer to the vision of a modernized authorizations platform. Software Engineer III leads the full software development lifecycle, ensuring high reliability and efficiency through collaboration, innovative solutions, and rigorous code standards. Requirements: - Master’s or bachelor’s degree in computer science, Information Systems, Engineering, or a related technical field or equivalent practical experience development practices. - At least 7+ years of hands-on experience in design and coding in Java, SpringBoot, Kafka, Junits, Mockito, Integration testing, Sonar Cube, REST, Cloud & related experience in docker, kubernetes, Helm config, Dynatrace, performance tuning for sub second response applications. - Experience working with relational and NoSQL databases such as Oracle, PostgreSQL, Cassandra, or similar technologies. - Hands-on experience with automated build and release management tools such as Git, Gradle/Maven, and CI/CD platforms (e.g., Jenkins or similar). - Strong understanding of software engineering fundamentals including code quality, testing, and performance optimization. - Demonstrated ability to proactively identify opportunities for system improvements and technical innovation. - Strong communication and collaboration skills with the ability to work effectively across teams and influence technical outcomes. - Willingness to continuously learn and adopt new technologies, tools, and engineering practices. - Familiarity with AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, or similar) to improve development productivity and code quality. - Experience with public cloud like GCP/AWS. Responsibilities: - Contribute as an active member of an Agile development team, driving consistent engineering practices related to development standards, testing, documentation, and shared tooling. - Design, develop, and maintain high-quality Java-based applications and services, dedicating majority of time (80%+) to coding, unit testing, and automated test development within sprint cycles. - Build and enhance scalable microservices and APIs that support fraud risk assessment and secure customer transaction processing. - Develop and optimize high-throughput data pipelines to improve system efficiency, reliability, and scalability. - Collaborate with cross-functional engineering teams and stakeholders to deliver multi-system initiatives and platform integrations. - Design, implement, and maintain CI/CD pipelines to support continuous integration, automated testing, and reliable software delivery. - Develop automation frameworks for application build, deployment, and operational processes to improve release velocity and system stability. - Build a deep understanding of system architecture and integrations across platforms within the supported business domain. - Continuously refactor and improve code quality, maintainability, and performance while applying modern software engineering best practices. - Identify opportunities to adopt innovative technologies, frameworks, and engineering approaches that improve development productivity and system quality. - Provide operational support for applications to ensure high availability, reliability, and performance in production environments. - Collaborate effectively across teams to drive engineering excellence, influence technical decisions, and challenge the status quo with a continuous improvement mindset. - Leverage modern developer productivity tools, including Generative AI-assisted development tools, to accelerate coding, debugging, documentation, and testing while maintaining high standards of code quality and security. - Utilize AI-powered engineering tools to assist in code generation, test automation, documentation, and system analysis to improve engineering efficiency.