Senior Solution Architect — Sales AI Applications

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

Responsibilities

• Guide technical solutions across front-end and back-end applications, APIs, data services, integrations, and cloud infrastructure. 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. Design for performance, availability, observability, security, scalability, and long-term maintainability.
• Lead technical design discussions, assess implementation options and emerging technologies, and make architecture decisions. Improve testing, code quality, continuous integration and delivery, monitoring, documentation, and production readiness. Resolve complex reliability and user-experience issues, mentor engineers, and contribute to engineering standards.

Requirements

• 10+ years of professional software engineering experience, including building and operating production applications. Experience with full-stack development and modern front-end, back-end, and web technologies; proficiency in one or more languages or frameworks such as Python, Java, JavaScript, React, or Node.js.
• Experience designing APIs, distributed applications, data services, enterprise integrations, scalable cloud applications, databases, and messaging systems, and 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. A bachelor’s degree or equivalent experience in Computer Science, Engineering, or a related field is encouraged.

Preferred

• Experience with generative AI applications, 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; taking AI capabilities from prototype to production alongside software systems and data pipelines.
• Familiarity with responsible AI, privacy, access controls, enterprise AI governance, Kubernetes, containers, microservices, infrastructure as code, DevOps, application performance and reliability, cloud cost efficiency, or globally distributed engineering teams.