英伟达Senior Software Engineer - MarTech Platform Development

任职要求

• Working proficiency in English. Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent experience, with 8+ years of relevant software engineering experience.
• Hands-on full-stack development with frontend frameworks, backend services, REST APIs, OIDC/RBAC concepts, databases, scripts, and platform integrations.
• Experience building or supporting data synchronization, API-driven workflows, data cleaning, integrity testing, performance checks, and production debugging.
• Ability to turn ambiguous requirements into practical technical designs, sequence diagrams, tasks, estimates, blockers, and release-ready execution plans.
• Clear communication across marketing, QA, operations, vendors, and global engineering partners.
• Demonstrated ability as a meticulous problem-solver with strong analytical skills, capable of diagnosing and resolving complex technical challenges under pressure.
• Strong awareness of China data privacy, data security, access control, credential handling, code security…

工作职责

NVIDIA is seeking a Senior Software Engineer to deliver hands-on engineering work for China digital marketing platforms across frontend, backend, APIs, connected systems, data workflows, and AI-powered automation. This role focuses on building reliable, testable, and maintainable features, tools, and integrations from technical design through implementation, release, and production support.
What you’ll be doing
• Build and maintain full-stack capabilities for NVIDIA.cn, campaign pages, registration flows, forms, microservice APIs, and China-specific digital marketing integrations.
• Develop reliable data sync workflows across platform APIs, scripts, marketing databases, CDP/segmentation flows, email/SMS activation, and analytics tagging.
• Support keynote and event experiences, including video delivery workflows, onsite check-in tools, QA readiness, troubleshooting, and production support.
• Translate marketing, compliance, and operations requirements into clear technical designs, sequence flows, data flows, tasks, risks, and testable acceptance criteria.
• Strengthen code quality, security, reliability, and maintainability through debugging, code review, access-control awareness, CI/CD, logging, and regression coverage.
• Use AI-assisted development and automation to improve content validation, QA efficiency, ticket workflows, paid-search operations, and team productivity.