Senior Solution Architect – Sales AI Applications
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Job Description
Senior Solution Architect building secure, scalable generative AI sales applications at NVIDIA. Designing full-stack architectures and integrating AI workflows into global enterprise sales experiences.
Responsibilities:
- 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 supporting performance, availability, observability, security, scalability, and long-term maintainability
- Lead technical design discussions, compare implementation approaches, make architecture decisions, and evaluate emerging technologies
- Improve testing, code quality, continuous integration and delivery, monitoring, documentation, and production readiness
- Investigate complex issues and develop solutions improving reliability and user experience
- Mentor engineers, share technical knowledge, and contribute to engineering standards and collaborative team practices
Requirements:
- 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
- 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
Benefits:
- NVIDIA is described as one of the technology world’s most desirable employers
- Opportunity to work on meaningful business problems and Sales AI applications
- Opportunity to collaborate with global, cross-functional teams
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