Software Engineering Intern

Type: Internship Location: Singapore Remote-friendly Eligibility: Undergraduate students currently in their 2nd or 3rd year (Sophomore or Junior) About the RoleWe 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