J&D Tech – AI Engineer – Multi-Agent Quant Trading Systems

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