Software Solutions Architect, NVIS

Summary

NVIDIA is a technology company developing accelerated computing and AI infrastructure solutions. The Software Solutions Architect will lead the development and productionization of agentic AI solutions for the NVIS delivery organization, including LLM-based agents, APIs, data pipelines, and automation workflows. The role will also integrate AI systems with enterprise platforms and collaborate across engineering, product, DevOps/SRE, and field teams to deliver reliable, scalable solutions.

Responsibilities

• 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

Skills

• B.Sc. degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field
• 5+ 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
• 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

Qualifications

Must Haves

• B.Sc. degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field
• 5+ 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

Nice to Haves

• 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

Benefits

• You will also be eligible for equity.