New The Skills of Tomorrow: how AI-exposed is every skill in 2026? See the data →
NVIDIA

Senior Software Engineer, Platform Engineering

NVIDIA
Apply →
onsite senior full-time $150,000 - $250,000 per year Santa Clara

First indexed 17 May 2026

Description

We are looking for a deeply technical, creative, and hands-on Senior Full-Stack Software Engineer to build the next generation AI platforms and products that improve business efficiency and productivity.

As a key leader in our technology team, you will play a pivotal role in shaping the architecture, development, and scaling of our software systems. This role will give an opportunity to collaborate with Cloud, AI/ML & Generative AI workforce in a multifaceted and agile working environment, while meeting the immediate and evolving needs of our business.

Responsibilities:

  • Hands-on experience with test automation, production testing, and automation frameworks
  • Solid understanding of Linux, embedded systems, firmware, and hardware/software integration
  • Deep knowledge of IT Service Management (ITSM) and ServiceNow (HR, Security, Finance modules preferred)
  • Collaborate with cross-functional teams to deliver end-to-end intelligent experiences across applications
  • Integrate agents with enterprise data sources, APIs, and internal microservices to enable real-world actions
  • Architect and build agentic AI systems that leverage LLMs for reasoning, planning, and tool orchestration across enterprise workflows
  • Develop scalable platforms for retrieval-augmented generation (RAG), long-term memory, and contextual reasoning
  • Build reusable infrastructure for agent orchestration, tool integration, evaluation, and observability

Requirements:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience)
  • 8+ years of experience building large-scale distributed systems and cloud-native applications (Python preferred)
  • Strong experience designing and deploying LLM-powered systems, including RAG, tool use, and agent-based architectures
  • Deep understanding of agentic AI paradigms (planning, memory, tool invocation, multi-step reasoning)
  • Experience with agent frameworks and orchestration tools (e.g., LangChain or similar)
  • Proven ability to design systems with high reliability, scalability, and performance
  • Hands-on experience deploying applications in Kubernetes environments
  • Experience building systems in cloud and hybrid environments
  • Strong programming skills across multiple languages and modern software stacks
  • Proven track record leading complex technical initiatives and mentoring high-performing teams

Benefits:

  • Eligible for equity
  • Comprehensive benefits package