Senior Software Engineer, Customer Data and Marketing AI

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. They are looking for an outstanding Senior Platform Engineer to help build the platforms that power customer data, digital marketing, personalization, and AI-enabled marketing workflows.

Responsibilities:

• Design, develop, and operate scalable backend services for customer profile, consent, personalization, campaign, and marketing platform capabilities
• Build data-intensive services that integrate with document or NoSQL databases, relational databases, caching layers, search platforms, object storage, and messaging, pub-sub, or event-driven systems
• Develop clean APIs, service-to-service integrations, authentication patterns, error handling, logging, caching, and reusable platform libraries
• Contribute to customer data platform workflows, including audience activation, downstream system synchronization, campaign metadata, tracking, and data observability
• Partner with marketing, product, analytics, data engineering, and AI platform teams to translate business needs into reliable technical solutions
• Modernize existing platforms across database models, identity systems, profile services, consent workflows, and operational tooling
• Apply AI-assisted engineering practices while maintaining strong ownership of architecture, testing, security, code quality, and production readiness
• Improve reliability through observability, alerting, automation, anomaly detection, and practical incident prevention

Requirements:

• BS in Computer Science, Engineering, or a related technical field, or equivalent experience
• 8+ years of software engineering experience building backend services, APIs, data platforms, and production systems
• Strong experience with one or more modern programming languages like Java, Python or Go, along with microservices architecture, and API design
• Hands-on experience with document or NoSQL database design, indexing, migration patterns, performance tuning, and operational best practices
• Experience with relational databases, SQL, distributed systems, cloud infrastructure, and containerized production environments
• Experience building systems that move customer, behavioral, consent, campaign, or audience data across platforms with strong attention to data quality, governance, and reliability
• Familiarity with caching, search, messaging, pub-sub, object storage, CI/CD, observability, and production operations
• Experience using AI-assisted engineering workflows responsibly while maintaining ownership of design, correctness, testing, security, and production readiness
• Self-motivated and collaborative, with the ability to own complex projects, drive progress independently, and communicate technical tradeoffs clearly across distributed teams
• Working knowledge of GDPR, PIPL, and related data privacy compliance and regulatory practices
• Experience building or operating customer data platforms, identity resolution systems, customer 360/profile services, consent platforms, audience activation workflows, personalization engines, or marketing activation systems
• Experience modernizing backend or data services that handle customer, audience, consent, or campaign data, including data model evolution, database migrations, and production cutovers
• Strong understanding of reliable customer data activation, including data quality, governance, consent enforcement, synchronization, recovery, and downstream reconciliation
• Experience applying AI or LLM-based systems to audience intelligence, personalization, campaign operations, content workflows, data discovery, or platform automation