As a Software Solution Architect, NVIS at NVIDIA, you will lead the transformation of AI infrastructure. Our NVIS team focuses on developing the next generation of NVIS Central, an agentic software platform with tools, services, and AI agents that automate, simplify, and speed up the work of our delivery organization. This role offers an outstanding chance to create and build LLM-powered agents that improve execution visibility, cut down manual tasks, and standardize workflows. These efforts allow NVIS to grow quickly and with high quality. Join us to bring up, validate, optimize, and upgrade large-scale AI Factory infrastructure for some of the world’s most advanced accelerated computing environments!
What you'll be doing:
Compose, build, and productionize agentic AI solutions, tools, and applications for the NVIS delivery organization.
Develop LLM-based agents, skills, tool-calling workflows, orchestration logic, backend services, APIs, data pipelines, and automation features as part of NVIS Central.
Translate field, delivery, operations, and product needs into clear technical builds, agent workflows, and working software.
Develop agents that can reason across project data, knowledge bases, operational systems, logs, reports, and delivery workflows.
Build workflows that help NVIS teams identify risks, summarize project status, automate repetitive tasks, improve readiness visibility, and simplify handoffs.
Work with timely engineering, retrieval-augmented generation, context management, agent memory, function calling, evaluations, and guardrails to build reliable AI systems.
Integrate LLMs and agents with internal systems, project data sources, knowledge repositories, reporting tools, and operational workflows.
Collaborate closely with software developers, architects, product managers, DevOps/SRE, and NVIS field teams to successfully implement reliable and scalable solutions.
Contribute to engineering guidelines, including code quality, testing, CI/CD, observability, documentation, security, and production support.
What we need to see:
B.Sc. degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field.
2+ years of hands-on software development experience building production applications, platforms, automation tools, or AI-based systems.
Strong programming experience with Python and modern backend development.
Hands-on experience working with LLMs, agentic workflows, timely composition, tool/function calling, RAG, and AI application development.
Experience crafting and implementing RESTful APIs, data services, workflow automation, and integrations with enterprise systems.
Experience building reliable software around non-deterministic AI systems, including testing, evaluation, monitoring, and failure handling.
Experience with Docker, Kubernetes, CI/CD, Git, observability, and cloud-native development practices.
Background with SQL and NoSQL databases, data modeling, querying, indexing, and data integration.
Excellent problem-solving skills, ownership attitude, and ability to operate in a fast paced, cross-functional environment.
Ways to stand out from the crowd:
Experience building agent platforms, copilots, multi-agent systems, tool-calling workflows, evaluation frameworks, or MCP-style integrations.
Deep understanding of LLM application patterns such as context engineering, retrieval quality, timely/version management, agent planning, human-in-the-loop workflows, and AI safety guardrails.
Experience with AI infrastructure, HPC clusters, NVIDIA DGX systems, SuperPOD, Spectrum-X, Ethernet, InfiniBand, Kubernetes, or SLURM.
Experience in automating workflows related to field, delivery, operations, or professional services.
Strong Linux, networking, security, SRE, or distributed systems background.
Skills Required
- B.Sc. degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field
- 2+ years of hands-on software development experience building production applications, platforms, automation tools, or AI-based systems
- Strong programming experience with Python and modern backend development
- Hands-on experience with LLMs, agentic workflows, tool or function calling, RAG, and AI application development
- Experience building RESTful APIs, data services, workflow automation, and enterprise-system integrations
- Experience testing, evaluating, monitoring, and handling failures in software using non-deterministic AI systems
- Experience with Docker, Kubernetes, CI/CD, Git, observability, and cloud-native development practices
- Experience with SQL and NoSQL databases, data modeling, querying, indexing, and data integration
- Excellent problem-solving skills, ownership attitude, and ability to work in a fast-paced, cross-functional environment
- Experience building agent platforms, copilots, multi-agent systems, tool-calling workflows, evaluation frameworks, or MCP-style integrations
- Deep understanding of LLM application patterns, including context engineering, retrieval quality, version management, agent planning, human-in-the-loop workflows, and AI safety guardrails
- Experience with AI infrastructure, HPC clusters, NVIDIA DGX systems, SuperPOD, Spectrum-X, Ethernet, InfiniBand, Kubernetes, or SLURM
- Experience automating field, delivery, operations, or professional-services workflows
- Strong Linux, networking, security, SRE, or distributed-systems background
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
