Senior Full Stack Software Engineer, Marketing Platforms

NVIDIA•Santa Clara, CA

10d•$224,000 - $356,500

About The Position

NVIDIA is seeking a Senior Software Engineer with deep backend engineering experience to design, build, and operate platforms supporting NVIDIA Marketing. The role owns scalable backend services, distributed systems, and data integrations for customer profiles, consent, personalization, and campaign operations, with hands-on responsibility spanning architecture, development, deployment, and production operations. The engineer will collaborate with product, design, marketing, partner teams, and other engineers to translate business needs into technical solutions and establish technical standards. The position also involves building responsive and accessible user interfaces connected to platform APIs, making architecture and delivery decisions, mentoring engineers, and maintaining production readiness and reliability. The engineer will develop specialized knowledge in applied AI and help support AI-enabled features and agents as product needs evolve. NVIDIA states that the role is an existing vacancy and that applications will be accepted at least until November 3, 2026.

Requirements

BS/MS in Computer Science, Engineering, or a related technical field, or equivalent experience.
12+ years of software engineering experience, including substantial ownership of production backend services.
Deep knowledge of distributed systems and scalable architecture, including service decomposition, concurrency, consistency, asynchronous processing, caching, fault tolerance, and resilience.
Strong hands-on backend development skills in Java with Spring Boot or a comparable framework, including API development, authentication, authorization, and service-to-service integration.
Solid database knowledge, including SQL, relational and NoSQL data modeling, indexing, transactions, schema migrations, and performance tuning.
Experience operating production services on cloud infrastructure using containers, automated testing, Git, CI/CD pipelines, observability, and detailed debugging to maintain reliability and performance.
Hands-on frontend development skills in JavaScript/TypeScript and React or Angular, including component building, state management, API integration, and responsive, accessible interfaces.
Demonstrated technical leadership and end-to-end ownership, including turning ambiguous requirements into architecture and delivery plans, driving cross-team projects, communicating tradeoffs, and mentoring engineers.
Enthusiasm for AI-based applications and readiness to learn and assist with AI feature and agent development; prior AI or ML experience is not essential.

Nice To Haves

Experience scaling high-throughput or low-latency services through load testing, profiling, query optimization, caching, and capacity planning.
Background with customer data platforms, identity resolution, consent management, audience activation, or personalization, including privacy practices for user data.
Experience with AWS or another major cloud platform, Kubernetes, messaging or streaming platforms, and complex service or database migrations.
Experience building enterprise web applications or reusable UI components and using automated checks and tools such as Selenium, Cucumber, Playwright, or Cypress.
Background with Python, AI-powered applications, LLMs, retrieval-augmented generation, tool-using agents, recommendations, or NVIDIA AI software.

Responsibilities

Architect, develop, and operate scalable backend services and distributed systems for customer profiles, consent, personalization, and campaign operations.
Build APIs, service boundaries, data models, and event-driven workflows, balancing consistency, availability, latency, efficiency, and operational complexity.
Develop data integrations using relational and NoSQL databases, messaging systems, caching, and search, with attention to data integrity, schema evolution, and failure recovery.
Develop responsive, accessible user interfaces and integrate them with platform APIs for data exploration, configuration, and marketing workflows.
Lead architecture decisions, align partner teams on interfaces and integration plans, and mentor engineers through building and code reviews.
Partner with product, design, and marketing teams to translate business needs into technical solutions.
Own production readiness and operations, including automated testing, CI/CD, deployments, observability, security, capacity planning, and incident resolution.
Modernize services through safe migrations and rollouts.
Develop specialized knowledge in applied AI and support development of AI-enabled features and agents, connecting platform APIs, data sources, and user workflows.