Intern, AI Engineer at Grab

Get to Know the Team You will be joining the Metadata & BI Platforms team within Grab's Data Engineering Platforms department. The team builds and maintains the systems that power Grab's data intelligence: Hubble (data discovery platform), Genchi (data observability platform), Superset and Power BI (business intelligence platforms), and the Data Agent (agentic analytics platform). We work at the intersection of data engineering and AI, building systems that help thousands of internal users across Grab discover, understand, and act on data. The team is passionate about applying the latest AI advances to make data more accessible, intelligent, and useful at scale. Get to Know the Role As an AI Engineer Intern, you will contribute to building and improving AI-powered data platforms that make data discovery, observability, and analytics smarter and more intuitive at Grab. You will get hands-on experience building production-grade systems — from LLM integrations and agentic workflows to vector search pipelines — alongside engineers who ship AI features at scale. This is a high-impact role where your contributions will be used by real internal users across the company. You will work in a fast-paced, collaborative environment with mentorship from experienced engineers, gaining exposure to the full AI product development lifecycle from design to deployment. The Critical Tasks You Will Perform • You will design and implement backend services and APIs that support AI-driven data platform features. • You will integrate LLM APIs into platform workflows to enable intelligent automation and natural-language capabilities. • You will contribute to building and orchestrating agentic systems (e.g., using LangGraph) for use cases such as data troubleshooting, SQL/code generation, and data Q&A. • You will develop and optimize vector search and RAG pipelines to improve data retrieval and semantic understanding. • You will debug and resolve performance or reliability issues in complex data systems, working toward production readiness. • You will Collaborate with product managers, data engineers, and data analysts to deliver high-impact features.