Software Engineering Intern, AI Agents and Backend Infrastructure

NVIDIA is looking for a Software Engineering Intern to join a team that builds infrastructure and agentic AI services for teams across the company. Our job is to remove other teams' bottlenecks: we build and run core internal services that power large geo-distributed infrastructure, and a growing share of what we ship is driven by AI agents. As an intern, you will work alongside senior engineers to design, build, and ship production systems – from backend services that run automated workflows at massive scale to AI agents that take routine work off engineers' plates. This is an excellent opportunity to gain hands-on experience with agentic AI and modern infrastructure while contributing to real products used by teams across NVIDIA.

What you'll be doing:

• Work with senior engineers to design, build, and improve backend services and APIs for internal platforms that run automated workflows at massive scale
• Build AI agents and agentic workflows that connect LLMs to tools and internal services, and integrate them into production systems
• Help make agents reliable and safe in production – from access control and guardrails to evaluating agent quality
• Assist in building data pipelines and GPU job orchestration for synthetic data generation and model evaluation at scale
• Implement and improve observability (tracing, metrics, logging) for distributed services and agents
• Participate in code reviews, testing, and debugging, and apply software engineering best practices in a production environment
• Work in a product-minded way: talk to internal users, prototype quickly, collect feedback, and iterate

What we need to see:

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Engineering, or related field
• Strong programming fundamentals in at least one of: Go (preferred), Python, or C#
• Solid understanding of data structures and algorithms
• Basic knowledge of software design patterns and API design concepts
• Hands-on experience building with LLMs – for example, a project, prototype, or coursework that uses LLM APIs
• Familiarity with version control systems (Git)
• Understanding of database concepts and SQL
• Strong problem-solving skills and eagerness to learn new technologies
• Excellent communication skills and ability to work effectively in a team environment

Ways to stand out from the crowd:

• Experience building AI agents or LLM-powered applications: tool/function calling, MCP, RAG, or agent frameworks (e.g., LangGraph, NVIDIA NeMo Agent Toolkit)
• Experience with distributed systems concepts (REST APIs, microservices architecture) and containerization (Docker)
• Knowledge of cloud platforms (AWS, GCP, Azure), GPU workloads, and infrastructure automation
• Familiarity with CI/CD pipelines, DevOps practices, observability tools (OpenTelemetry, Prometheus, Grafana), and orchestration platforms (Kubernetes)
• Experience with database technologies (MySQL, MongoDB, Redis, Elasticsearch)