AI Efficiency Engineering Intern
Beijing-based enterprise AI company building foundation-model, agentic-AI, and AI-transformation products, including the TrueNorth enterprise decision hub.
Funding history
Investors
About 01.AI
01.AI develops full-stack enterprise AI solutions, industry-agent applications, and sovereign/industry model-training capabilities.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will contribute to full-stack development of an enterprise AI efficiency platform, turning organizational, engineering, and operational needs into reliable platform capabilities. You will help build frontend and backend services, AI tools, internal data and permission management, system integrations, and AI capability integrations. You will create isolated workspaces using containers or sandboxes, support code retrieval, dependency setup, and execution artifacts, and explore AI agent applications including tool calling, context management, validation, and risk control. You will collaborate with business stakeholders, design and deliver solutions, iterate from internal user feedback and operational data, and develop reusable engineering capabilities for secure platform evolution.
Requirements
- Be a 2027 undergraduate student or above, preferably in computer science, software engineering, or a related field
- Demonstrate strong programming fundamentals
- Know at least one of Rust, Python, or Go; Rust experience is preferred
- Be willing to collaborate on full-stack development
- Be available to intern at least four days per week for at least six consecutive months
- Be able to start as soon as possible
- Demonstrate engineering practices, technical-documentation research skills, problem analysis, and independent problem-solving ability
Responsibilities
- Develop full-stack capabilities for an enterprise AI efficiency platform
- Build frontend and backend services, AI tools, data and permission management, system integrations, and AI integrations
- Create isolated workspaces with containers or sandboxes and handle code retrieval, dependency setup, and execution artifacts
- Explore enterprise AI agent applications, including tool calling, context management, validation, and risk control
- Collaborate with business stakeholders to design, deliver, and iterate solutions using user feedback and operational data
- Research large-model application engineering and full-stack development practices and build reusable engineering capabilities