Senior Full Stack Software Engineer, Marketing Platforms

Posted 2 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
224K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design, build, and operate scalable backend services, distributed systems, APIs, data integrations, and marketing platforms. Develop responsive frontend interfaces, lead architecture decisions, mentor engineers, and collaborate with product, design, and marketing teams. Own production readiness, CI/CD, observability, security, deployments, capacity planning, and incident response. Support AI-enabled features while maintaining reliable customer profile, consent, personalization, and campaign workflows.
Summary Generated by Built In

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.


We are looking for a Senior Software Engineer with deep backend engineering experience to design, build, and operate the platforms supporting NVIDIA Marketing. You will own scalable backend services, distributed systems, and data integrations for customer profiles, consent, personalization, and campaign operations. This is a hands-on role with ownership from architecture and development through deployment and production operations. Collaborate with passionate professionals in an inclusive environment as you push boundaries and establish new technological standards


What you'll be doing:

  • 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, making clear tradeoffs across consistency, availability, latency, efficiency, and operational complexity.
  • Develop dependable data integrations employing relational and NoSQL databases, messaging systems, caching, and search, focusing on data integrity, schema evolution, and failure recovery.
  • Develop responsive, accessible user interfaces and integrate them with platform APIs to support 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 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.
  • Gain specialized knowledge in applied AI and support the development of AI-enabled features and agents as product demands shift, connecting platform APIs, data sources, and user workflows.

What we need to see:

  • BS/MS in Computer Science, Engineering, or a related technical field, or equivalent experience
  • 12+ years of software engineering experience, with 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 building, 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: independently turning ambiguous requirements into architecture and delivery plans, driving projects across teams, communicating tradeoffs, and mentoring engineers.
  • Enthusiasm for AI-based applications and a readiness to learn and assist in AI feature and agent development. Prior experience in AI or ML is not essential.

Ways to stand out from the crowd:

  • 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, applying development techniques that ensure functionality through 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.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 23, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Skills Required

  • BS/MS in Computer Science, Engineering, or a related technical field, or equivalent experience
  • 12+ years of software engineering experience with 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
  • Hands-on backend development experience in Java with Spring Boot or a comparable framework
  • Experience building APIs, authentication, authorization, and service-to-service integrations
  • Database expertise including SQL, relational and NoSQL data modeling, indexing, transactions, schema migrations, and performance tuning
  • Experience operating production services on cloud infrastructure with containers, automated testing, Git, CI/CD pipelines, observability, and debugging
  • Hands-on frontend development experience with JavaScript or TypeScript and React or Angular
  • Experience with component building, state management, API integration, and responsive accessible interfaces
  • Demonstrated technical leadership and end-to-end ownership, including architecture planning, cross-team delivery, tradeoff communication, and mentoring
  • Experience scaling high-throughput or low-latency services through load testing, profiling, query optimization, caching, and capacity planning
  • Experience with customer data platforms, identity resolution, consent management, audience activation, or personalization
  • 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 with automated testing 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

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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