We are a next-generation quant trading startup with a singular mission: to conquer the US stock market using AI-first systems. Founded by traders and engineers, we operate at the intersection of finance, machine learning, and high-performance computing. Our edge comes from deep contextual understanding, self-improving multi-agent architectures, and a relentless focus on generating real, quantifiable alpha in small-cap equities. We are building a fully automated hedge fund, where every decision is driven by intelligence — not guesswork.
Role Overview
As an AI Engineer Intern, you’ll be part of the core team building an agentic AI infrastructure that can:
Generate new trading features using methods like analogy, reverse engineering, and brute-force composition
Classify and tag those features into meaningful groups
Validate logic, backtest results, and determine what works
Autonomously write and debug trading strategy code in C++/Python
Create and manage a growing feature and strategy library with real P&L attribution
Continuously improve itself through feedback loops and structured memory
You won’t just be tweaking models — you’ll be building intelligent agents that outthink the market.
What You'll Do
Help design and implement multi-agent workflows using Claude, GPT, and open-source LLMs
Build Python tools for prompt chaining, agent task orchestration, and validation pipelines
Design test frameworks for checking whether a generated feature matches its description
Write evaluation logic to measure correlation between generated features and trading P&L
Work with traders and developers to integrate AI outputs into the live strategy framework
Brainstorm and iterate on new ways to create, test, and deploy trading logic automatically
Requirements
Must-Have:
Passion for AI, LLMs, and financial markets
Strong Python skills and familiarity with LangChain / OpenAI / Claude APIs
Curious, fast learner, and comfortable working in an ambiguous, high-speed environment
Understanding of prompt design, task decomposition, or agentic workflows
Interest in quantitative finance, trading strategies, or market microstructure
Nice-to-Have:
Exposure to C++ (for quant strategy integration)
Familiarity with small-cap equity trading, backtesting, or trading system design
Experience working on LLM planning, memory, or self-reflection frameworks
Experience with real-world prompt failures and debugging generative output mismatches
What You’ll Gain
Real-world experience building cutting-edge agentic AI systems for quant trading
Exposure to the end-to-end lifecycle of a fully automated trading system
Mentorship from experienced quants, traders, and AI engineers
Opportunity to work on high-impact projects — your code could directly affect live P&L
Fast feedback loops, full ownership, and no red tape
To Apply
Send your resume, GitHub/portfolio, and a short note on why you're interested in agentic AI for trading to [your email/contact]. Bonus: include one AI idea that could help a trading system get smarter.
If you’re the kind of person who reads GPT papers and watches stock tickers for fun — you’ll fit right in
Kindly note that only shortlisted candidates will be notified.
Related Job Searches:
- Company:
J&D Tech - Designation:
AI Engineer – Multi-Agent Quant Trading Systems - Profession:
Engineering - Industry:
Finance - Location:
Bukit Merah