DatabricksNew York City, New York$200k-$265k3h ago
NVIDIAPosted 3w ago
Senior Solution Architect — Sales AI Applications at NVIDIA scores 80 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
Design and build scalable full-stack applications integrating generative AI and agentic workflows for enterprise sales.
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.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- How do you think about the risk of an AI system in this kind of role failing silently?
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, Rag, AI Agents, AI Evaluation, and AI Safety. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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