Senior Solution Architect — Sales AI Applications
Nvidia
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This role on the market
365 open applications roles across 96 companies are on ApplySarthi right now, most of them in Bengaluru (21), Hyderabad (9), Pune (2).
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What applications roles keep asking for: Python (21%) — counted across their open postings here.
Solutions Architect jobs in India · Remote Solutions Architect jobs · Generative AI jobs · Java jobs · JavaScript jobs · Kubernetes jobs
Nvidia has 2,788 open roles listed here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for applications roles keep coming back to Python. Practise those questions before you sit with Nvidia.
Questions you are likely to be asked
- Why do you want to join Nvidia?
- What is your experience with Generative AI? Tell me one thing you learned the hard way.
- Walk me through a deal you closed, from the first call.
- Tell me about a deal you lost. What would you do differently?
- How do you handle 'your price is too high'?
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Practise the Senior Solution Architect — Sales AI Applications at Nvidia interview free →NVIDIA pioneers computer graphics, gaming, AI, and accelerated computing. We are looking for a Senior Solution Architect with full-stack software engineering experience to join our team and play an important role in developing Sales AI applications. This position offers the opportunity to design, build, and evolve solutions that bring generative AI and intelligent workflows into everyday sales experiences. 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.
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Listed on workday · posted 2026-10-14. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.