AI Engineer - Multi-Agent Quant Trading Systems

J&D Tech

  • Bukit Merah, Singapore
  • $1,200-2,550 per month
  • Permanent
  • Full-time
  • 1 month ago
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.Job DescriptionRole OverviewAs 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 compositionClassify and tag those features into meaningful groupsValidate logic, backtest results, and determine what worksAutonomously write and debug trading strategy code in C++/PythonCreate and manage a growing feature and strategy library with real P&L attributionContinuously improve itself through feedback loops and structured memoryYou won’t just be tweaking models — you’ll be building intelligent agents that outthink the market.What You'll DoHelp design and implement multi-agent workflows using Claude, GPT, and open-source LLMsBuild Python tools for prompt chaining, agent task orchestration, and validation pipelinesDesign test frameworks for checking whether a generated feature matches its descriptionWrite evaluation logic to measure correlation between generated features and trading P&LWork with traders and developers to integrate AI outputs into the live strategy frameworkBrainstorm and iterate on new ways to create, test, and deploy trading logic automaticallyRequirementsMust-Have:Passion for AI, LLMs, and financial marketsStrong Python skills and familiarity with LangChain / OpenAI / Claude APIsCurious, fast learner, and comfortable working in an ambiguous, high-speed environmentUnderstanding of prompt design, task decomposition, or agentic workflowsInterest in quantitative finance, trading strategies, or market microstructureNice-to-Have:Exposure to C++ (for quant strategy integration)Familiarity with small-cap equity trading, backtesting, or trading system designExperience working on LLM planning, memory, or self-reflection frameworksExperience with real-world prompt failures and debugging generative output mismatchesWhat You’ll GainReal-world experience building cutting-edge agentic AI systems for quant tradingExposure to the end-to-end lifecycle of a fully automated trading systemMentorship from experienced quants, traders, and AI engineersOpportunity to work on high-impact projects — your code could directly affect live P&LFast feedback loops, full ownership, and no red tapeTo ApplySend 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 inApplication InstructionsPlease apply for this position by submitting your text CV using InternSG.
Kindly note that only shortlisted candidates will be notified.

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