Software Engineering Intern jobs

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