Software Engineering Intern, AI Agents & Backend Infrastructure – 2027
NVIDIA is hiring a Software Engineering Intern, AI Agents & Backend Infrastructure – 2027 for a remote role open to applicants in Germany. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- This is listed as a remote role.
- The posting mentions LangGraph, RAG and AI agents among its tools and skills.
- NVIDIA has 2,700+ other open roles on Level.
- Posted in the last few days.
AI in this role
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)
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
How we rate this
Software Engineering Intern, AI Agents & Backend Infrastructure – 2027 at NVIDIA rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- What's a project where you used LangGraph hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, AI Evaluation, and LangGraph. 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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get new remote software engineering jobs (Builds AI ●●●●) by email
One email a week with the new remote software engineering jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Software Engineering roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step