Senior Solution Architect — Sales AI Applications

NVIDIA seeks a Senior Solution Architect to design, build and evolve Sales AI applications that bring generative AI and intelligent workflows into enterprise sales experiences. The role works across the application stack with Product, AI and machine learning, Data, Security, Solution Architecture and Engineering teams to deliver secure, reliable solutions used globally. The posting lists India, Pune and India, Remote as locations.

Responsibilities

• Design, develop and maintain scalable full-stack solutions for sales workflows, guiding front-end, back-end, API, data-service, integration and cloud-infrastructure decisions.
• Translate product and business requirements into maintainable solutions and intuitive user experiences. Integrate generative AI models, AI services, retrieval systems and agentic workflows into production applications.
• Lead technical design discussions and architecture decisions, considering performance, availability, observability, security, scalability and maintainability. Improve testing, code quality, continuous integration and delivery, monitoring, documentation and production readiness; investigate complex issues and mentor engineers.

Requirements

• 10+ years of professional software engineering experience, including building and operating production applications. A bachelor’s degree or equivalent experience in Computer Science, Engineering or a related technical field is encouraged.
• Full-stack development experience and proficiency in one or more technologies such as Python, Java, JavaScript, React or Node.js. Experience with APIs, distributed applications, data services, enterprise integrations, scalable cloud applications, databases and messaging systems.
• Experience integrating AI or machine learning through APIs, models, retrieval systems or AI services; knowledge of architecture, system design, security, testing, observability and production operations. Ability to lead initiatives, communicate across technical and non-technical teams, and mentor engineers.

Preferred

• Experience with generative AI applications, AI assistants, retrieval-augmented generation, agentic workflows, large language model APIs, vector databases, prompt engineering or AI evaluation, including taking AI capabilities from prototype to production.
• Familiarity with responsible AI, privacy, access controls or governance; Kubernetes, containers, microservices, infrastructure as code, DevOps, cloud cost efficiency or globally distributed engineering teams.