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NVIDIA

Software Engineering Intern, AI Agents, Backend Infrastructure

NVIDIA

. Design, build, and improve backend services and APIs for internal platforms running automated workflows at massive scale .

Posted 10/27/2026full-timeRemote • United KingdomEntry LevelWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates strong programming fundamentals in Go, Python, or C#, with hands-on experience in building AI agents and LLM-powered applications. Proficient in distributed systems, cloud platforms, and observability tools, while effectively collaborating in a team environment.

Highest-signal resume keywords
Programming Fundamentals in Go, Python, or C#Experience Building AI Agents or LLM-Powered ApplicationsUnderstanding of Distributed Systems ConceptsFamiliarity with Cloud Platforms (AWS, GCP, Azure)Knowledge of CI/CD Pipelines and DevOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Programming FundamentalsData Structures and AlgorithmsSoftware Design PatternsAPI Design ConceptsBuilding with LLMsDatabase Concepts and SQLDistributed Systems ConceptsContainerization (Docker)Database Technologies (MySQL, MongoDB, Redis, Elasticsearch)GPU Job Orchestration
Soft Skills
Strong Problem-Solving SkillsEagerness to Learn New TechnologiesExcellent Communication SkillsAbility to Work Effectively in a Team Environment
Tools & Technologies
Version Control Systems (Git)Observability Tools (OpenTelemetry, Prometheus, Grafana)Orchestration Platforms (Kubernetes)Cloud Platforms (AWS, GCP, Azure)
Industry Keywords
AI AgentsLLM APIsMicroservices ArchitectureREST APIsInfrastructure Automation

Tech Stack

Tools & technologies
AWSAzureCloudDistributed SystemsDockerElasticSearchGoogle Cloud PlatformGrafanaKubernetesMicroservicesMongoDBMySQLPrometheusPythonRedisSQLGo

About the role

Key responsibilities & impact
  • Design, build, and improve backend services and APIs for internal platforms running automated workflows at massive scale
  • Build AI agents and agentic workflows connecting LLMs to tools and internal services, and integrate them into production systems
  • Improve agent reliability and safety through access control, guardrails, and agent-quality evaluation
  • Assist with data pipelines and GPU job orchestration for synthetic data generation and model evaluation at scale
  • Implement and improve tracing, metrics, and logging for distributed services and agents
  • Participate in code reviews, testing, debugging, and production software engineering practices
  • Talk to internal users, prototype quickly, collect feedback, and iterate
  • Work alongside senior engineers on infrastructure and agentic AI services used by teams across NVIDIA

Requirements

What you’ll need
  • 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, such as a project, prototype, or coursework using 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
  • 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)

Benefits

Comp & perks
  • Competitive salaries
  • Generous benefits package
  • Equal opportunity employer
  • Diversity-valuing workplace