Data & AI Intern
StraitsX provides regulated stablecoin payment infrastructure for global fintechs and institutions using blockchain technology.
About StraitsX
StraitsX helps global fintechs and institutions build cross-border payment solutions using regulated stablecoins. Users can mint, redeem, and transfer stablecoins for multiple currencies, access programmable payment flows, and connect with banking partners across Southeast Asia. StraitsX operates under Major Payment Institution licenses from the Monetary Authority of Singapore.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will join the Data team as an Intern with an Agentic AI mindset for approximately 6 months. You will help develop AI Agents alongside colleagues in the Data team, learning how agentic systems can change how users interact with data. You will grow your skills alongside data analysts and software engineers in a fast-paced fintech environment, working on real production use cases involving AI-powered automation and data integration.
Requirements
- Currently pursuing or recently completed a degree in Computer Science, Software Engineering, or a related technical field
- Experience tinkering with tools such as Claude Code, Cursor, Kiro, or similar AI-native development tools
- Awareness of how such tools can have their capabilities expanded, e.g. through MCPs, Skills
- Familiarity with at least one backend language such as Python, Go, TypeScript, or Ruby
- Familiarity with Git for version control
- Experience with workflow orchestration tools such as n8n or LangChain is a bonus
- Familiarity with LLM APIs is a bonus
- Interest in Fintech, Crypto, or how money moves globally is a bonus
Responsibilities
- Participate in the development of AI-powered automations that streamline internal engineering and operational processes
- Support other data team members to design and implement agentic workflows
- Connect AI agents to critical internal data sources and APIs to enable data retrieval and processing for production use cases
- Support the full lifecycle of Retrieval-Augmented Generation (RAG) knowledge bases, including data ingestion, vectorization, and maintenance
- Maintain relevant internal data sources such as Notion, JIRA, and Slack logs
- Develop methods and dashboards to track and quantify the efficiency gains from deployed AI agents
- Build internal bots or proof-of-concepts that demonstrate the potential of agentic AI