Level

NVIDIA

Software Engineering Intern, DGX Cloud Test Development - 2027

NVIDIA is hiring a Software Engineering Intern, DGX Cloud Test Development - 2027 in Shanghai, China. Level rates it ; you can apply on Level.

AI in this role

Develop test frameworks and validate AI agents and cloud-native workflows as a software engineering intern.

pythonlinuxkubernetesdocker
prompt-engineeringragai-agentsai-evaluationsoftware-testingqallmscloud-native

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

What you’ll be doing:

  • Test NVIDIA AI agents and end-to-end agentic workflows across NV GPU Platform.
  • Design and execute functional, integration, end-to-end, reliability, performance, and security tests.
  • Develop automated tests and evaluation frameworks for capabilities such as reasoning, tool use, multi-turn interactions, memory, and retrieval.
  • Use AI development tools to improve productivity across test planning, test case development, execution, analysis, and automation.
  • Validate cloud-native AI service workflows across API endpoints, deployment, invocation, model serving, routing, streaming, autoscaling, cancellation, authorization, observability, and failure recovery.
  • Collaborate with development teams to triage issues, perform root-cause analysis, verify fixes, and improve test coverage and quality.

What we need to see:

  • Currently pursuing a master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
  • Strong software development potential, with proficiency in Python and shell scripting.
  • Familiarity with AI, machine learning, large language models, or AI agent technologies.
  • Experience using AI development tools to improve quality and productivity across the end-to-end QA workflow.
  • Good knowledge of Linux and software testing methodologies.
  • Familiarity with REST API testing and cloud-native service validation, such as deployment, invocation, authorization, streaming, observability, and failure handling.
  • Strong problem-solving, communication, and interpersonal skills.
  • Fluent written and spoken English.
  • A proactive, innovative, and self-motivated attitude with a passion for learning cutting-edge technologies.
  • Ability to work full-time, on-site five days per week, for one year.

Ways to stand out from the crowd:

  • Experience testing LLM applications, AI agents, or agentic workflows.
  • Experience developing AI evaluation or test automation frameworks.
  • Knowledge of RAG, tool calling, prompt engineering, or multi-agent systems.
  • Experience with Docker, Kubernetes, OpenStack, or other cloud-native technologies; familiarity with Go is a plus.
  • Experience with NVIDIA GPU hardware, CUDA, or parallel programming.

How we rate this

Software Engineering Intern, DGX Cloud Test Development - 2027 at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGAI agentsAI EvaluationSoftware TestingQaLLMsCloud Native

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How do you decide when an AI agent can act on its own versus asking for approval first?
  4. How do you decide that one model's output is better than another's for a given task?
  5. Tell me about a project where software testing was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, RAG, AI agents, AI Evaluation, and Software Testing. 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.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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