Type: Internship
Location: Singapore Remote-friendly
Eligibility: Undergraduate students currently in their 2nd or 3rd year (Sophomore or Junior)
About the Role
We build AI-native software products designed to solve real business problems.
This is not a traditional internship where you work on isolated tasks. You will partner directly with business stakeholders, take ownership of projects from idea to delivery, and help build practical AI-powered tools and workflows used by real users.
We are looking for builders - people who enjoy turning ideas into working products and are excited about applying AI to real-world challenges.
What You'll Do
- Own projects end-to-end: scope, build, test, iterate, and ship
- Work directly with business stakeholders to translate requirements into software solutions
- Design and implement AI-powered workflows, tools, and automations
- Build and integrate applications using LLMs, APIs, agents, and AI frameworks
- Evaluate prompts, models, and AI outputs to improve reliability and usability
- Document solutions and continuously improve them based on feedback
Requirements
- Currently pursuing a Bachelor's degree in Computer Science, Software Engineering, AI, or a related field
- Undergraduate student in Year 2 or Year 3 (Sophomore or Junior preferred)
- Strong Python programming skills
- Experience building or experimenting with LLM-based applications, AI agents, RAG systems, automations, or AI workflows
- Able to work independently and drive tasks to completion with limited supervision
- Strong problem-solving ability and willingness to learn quickly
- Good written and verbal English communication skills
Nice to Have
- Experience shipping personal projects, hackathon projects, or open-source contributions
- Familiarity with Git, GitHub, and modern software development workflows
- Experience with AI tools and frameworks such as OpenAI APIs, Claude, LangChain, CrewAI, AutoGen, or similar
- Exposure to cloud platforms and deployment tools
- Interest in finance, operations, SaaS, or business automation
What You'll Learn
- End-to-end project ownership: from requirements to deployment
- Practical AI engineering: tool selection, prompt design, evaluation, and iteration
- How to work effectively at the intersection of business and engineering
- Building and shipping AI-powered software in a production context
