About Us
We are a Hong Kong-based equity long-only fund managing US$1 billion in AUM. We employ a fundamental, research-driven, bottom-up investment process. To maintain our edge, we are building an internal AI-integrated research system designed to automate workflows, centralize intelligence, and improve research productivity and information processing efficiency.
The Role
We are seeking a highly capable, research-minded System Engineer Intern—ideally an advanced degree candidate in a quantitative field—to work directly alongside our investment team.
Your mandate is to architect the data orchestration and intelligence layer of our research system. Your value add will be in workflow automation, data extraction, and AI engineering—turning unstructured data from fragmented financial sources into structured, searchable institutional knowledge.
A monthly stipend is provided to support living expenses during the internship.
Core Responsibilities
- Design and maintain automated pipelines to capture and centralize information from diverse sources;
- Direct the automated conversion of all incoming data into standardized, high-quality OCR PDF formats;
- Architect and maintain a programmatic folder system that routes files accurately into specific industry and company repositories;
- Deploy Large Language Models (LLMs) to automatically generate structured insights, core takeaways, and briefs from newly ingested company data;
- Build monitoring tools to track specific business drivers and configure an internal alerting system that notifies the investment team when material information changes.
- Implement a Retrieval-Augmented Generation (RAG) conversational chatbot, allowing the investment team to interactively query and cross-reference the document repository.
- Engineer the alert and chat interfaces so that every insight or notification links directly back to both its source OCR PDF file and its corresponding AI summary page in a single click.
Requirements
- Currently pursuing an advanced degree in Computer Science, Data Science, Engineering, or a highly quantitative field.
- Strong Python development skills, with hands-on experience handling web scraping, API integrations, and automation hooks.
- Strong SQL skills and familiarity with document processing tools (e.g., OCR libraries, PDF parsers). Experience dealing with metadata tagging and source citation mapping is highly valued.
- Strong hands-on experience deploying and running open-source tools locally, managing local databases and setting up local system environments on standalone hardware.
- Experience applying LLM APIs, advanced prompt engineering, and Vector Databases / RAG frameworks to build conversational chatbot interfaces with accurate source citation mechanisms.
- Strong interest in public equity markets and fundamental investment research.
Interview Process
- Apply - Submit your resume and an optional cover letter highlighting an automation pipeline, a structured database project, or an LLM application you have built.
- Take-home Test - Promising applicants will be asked to complete a coding test based on real data ingestion challenge. Expect 2–3 hours of work.
- Interview - Candidates who pass the technical assessment will be invited to an on-site interview with our investment team.
- Decision - Successful candidate will be notified via email.
Pay: $8,000.00 - $10,000.00 per month
Work authorization:
Work Location: In person
