We are an AI-first quantitative trading fund building a fully automated, multi-agent research and execution ecosystem for trading U.S. small-cap equities, options, and crypto markets. Our edge lies in the fusion of quant research, AI autonomy, and high-performance infrastructure.
We’re looking for a Data Engineer Intern who will help design, optimize, and scale the data systems powering our AI and trading pipelines. You’ll work directly with quant researchers, C++ developers, and AI engineers to build the foundation that enables autonomous strategy discovery and execution.
Key Responsibilities
Data Infrastructure Development: Build and maintain scalable data pipelines for ingesting, transforming, and storing high-frequency market data (minute, tick, and L2).
Linux Systems Engineering: Manage and optimize processes across Linux servers (file systems, permissions, cron jobs, daemons, I/O optimization).
C++ Integration: Collaborate with developers to integrate C++ backtesting and data-processing modules into the broader data infrastructure.
Automation: Implement tools to automate data ingestion, cleaning, and synchronization across Python and C++ layers.
Multi-Agent Integration: Work with AI engineers to connect data pipelines into multi-agent research frameworks (feature generation, validation, and model retraining).
Performance Optimization: Benchmark system performance, identify bottlenecks, and improve throughput and reliability.
Monitoring & Validation: Build health checks and diagnostic dashboards for data quality and latency tracking.
Requirements
Strong knowledge of Linux systems, including shell scripting, environment setup, and process management.
Proficiency in C++ (data structures, file I/O, multithreading preferred).
Experience with Python (pandas, multiprocessing, or FastAPI) for ETL and data orchestration.
Understanding of databases (ClickHouse, PostgreSQL, or similar).
Basic familiarity with AI/ML workflows (LangChain, LLM agents, or data preparation for model training).
Strong understanding of data engineering principles: pipeline design, error handling, schema evolution, and versioning.
Interest in financial data and quantitative systems.
What You’ll Gain
Hands-on exposure to real-world AI-driven quant infrastructure.
Experience working on high-frequency, multi-language systems (C++/Python/Linux).
Direct mentorship from quant researchers and AI engineers building next-generation agentic systems.
Opportunity to contribute to live research and production-grade infrastructure.
Pathway to a full-time Data or Systems Engineer position upon strong performance.
Kindly note that only shortlisted candidates will be notified.
Related Job Searches:
- Company:
J&D Holdings - Designation:
Data Engineer Intern (AI & Multi-Agent Quant Systems) - Profession:
Engineering - Industry:
Finance - Location:
Bukit Merah