We are upgrading the traditional procurement system into an AI-native procurement platform, focusing on building Procurement Agents. You will work alongside experienced engineers at the frontier of AI Agent engineering, getting hands-on with real problems from day one, and receive mentorship to grow quickly.
Responsibilities
- Support the construction and exploration of Procurement Agents and the System AI Harness, contributing to feature design, implementation, and validation under the guidance of your mentor.
- Develop and maintain services, business logic, and data flows that power AI-native procurement, with attention to code quality and reliability.
- Explore AI Agent capabilities — such as planning, tool use, memory, and multi-step reasoning — and help turn them into working features that solve real procurement problems.
- Build quick prototypes, experiment with emerging AI techniques, and help translate promising ideas into practical product capabilities.
- Collaborate with product managers, designers, and engineers to break down problems and deliver complete solutions.
Requirements
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Minimum Qualifications
- Currently enrolled in a bachelor's, master's, or PhD program in Computer Science, Software Engineering, Artificial Intelligence, Data Science, Electronic/Information Engineering, Mathematics, or a related field, with a solid academic record.
- Able to intern for a continuous period (ideally 3 months or more) and available for at least 3 days per week.
- Solid foundation in data structures, algorithms, and software engineering fundamentals from coursework or projects.
- Proficiency in at least one programming language (Golang / Java / Python), with good coding habits.
- Strong logical thinking, fast learning ability, and excellent independent thinking and problem-breakdown skills.
- Genuine curiosity and passion for exploring and applying frontier AI technologies; prior professional work experience is not required.
Preferred Qualifications
- Coursework, research, or personal projects related to AI / machine learning / large language models.
- Prior internship, lab, open-source, or personal project experience demonstrating hands-on ownership of a non-trivial system (a strong plus, but not required).
- Exposure to LLM-based systems, prompt engineering, RAG, tool/function calling, or agent orchestration frameworks.
- Experience building small AI-powered applications, Agent-based demos, or developer productivity tools.
- Achievements in programming competitions (e.g., ACM/ICPC, Kaggle), research publications, or high-quality open-source contributions.
- A proactive, self-motivated mindset and strong drive to turn ideas into working products.