You will work across the application stack and collaborate with Product, AI and machine learning, Data, Security, Solution Architecture, and Engineering teams to deliver secure, reliable, and scalable solutions used globally.

What you’ll be doing:

• Collaborate with application teams to design, develop, and maintain scalable full-stack solutions for enterprise sales workflows.

• Guide technical solutions across front-end, back-end, APIs, data services, integrations, and cloud infrastructure.

• Translate product requirements and business needs into secure, maintainable solutions and intuitive user experiences.

• Integrate generative AI models, AI services, APIs, retrieval systems, and agentic workflows into production applications.

• Design application architectures that support performance, availability, observability, security, scalability, and long-term maintainability.

• Lead technical design discussions, compare implementation approaches, make informed architecture decisions, and evaluate emerging technologies.

• Improve engineering practices for testing, code quality, continuous integration and delivery, monitoring, documentation, and production readiness. Investigate complex issues and develop solutions that improve reliability and user experience.

• Mentor engineers, share technical knowledge, and contribute to engineering standards and collaborative team practices.

What we need to see:

• A bachelor’s degree or equivalent experience in Computer Science, Engineering, or a related technical field is encouraged.

• 10+ years of professional software engineering experience, including building and operating production applications.

• Experience developing full-stack applications with modern front-end, back-end, and web application technologies.

• Proficiency in one or more languages or frameworks, such as Python, Java, JavaScript, React, Node.js, or similar technologies.

• Experience designing APIs, distributed applications, data services, enterprise integrations, scalable cloud applications, databases, and messaging systems.

• Experience integrating AI or machine learning capabilities through APIs, models, retrieval systems, or AI services.

• Knowledge of software architecture, system design, security, testing, observability, and production operations.

• Ability to lead technical initiatives, make informed engineering decisions, communicate with technical and non-technical teams, and mentor engineers.

Ways to stand out from the crowd:

• Experience building generative AI applications, including AI assistants, retrieval-augmented generation, agentic workflows, AI productivity tools, Python-based AI services, large language model APIs, vector databases, prompt engineering, or AI evaluation.

• Experience combining traditional software systems with AI models and data pipelines and progressing AI capabilities from prototype through production.

• Familiarity with responsible AI, data privacy, access controls, security, or enterprise AI governance.

• Experience with Kubernetes, containers, microservices, infrastructure as code, DevOps practices, application performance, reliability, scalability, observability, cloud cost efficiency, or globally distributed engineering teams.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you’re creative, eager to tackle meaningful business problems, and enjoy having fun, NVIDIA is the perfect company to work for.