AI Engineer (Multi-Agentic Quant Systems)

Varsity Techlatenttechcorp.com; Singapore; On-site; SGD 48,000 - 72,000; Full time

Job summary

Varsity Techlatenttechcorp.com is looking for a Junior AI Engineer to join our multi-agent systems team in Singapore. You will design, implement, and maintain AI-driven agent workflows supporting quantitative research, backtesting engines, and live trading infrastructure.

You will work closely with senior engineers and quants to turn experimental ideas into production‑ready agents that generate measurable alpha, with a strong emphasis on rapid experimentation and robust code.

Qualifications

• Bachelor's degree in Computer Science, AI/ML, Data Science, or a related field.
• Proficiency in Python or C++ (bonus: both).
• Familiarity with agentic AI frameworks (LangChain, AutoGen, CrewAI, etc.) or willingness to learn.
• Knowledge of ML concepts, reinforcement learning, or multi-agent systems.

Responsibilities

• Develop and maintain multi-agent AI pipelines for feature generation, factor evaluation, and strategy testing.
• Implement autonomous agent behaviors for data ingestion, strategy induction, and trade log analysis.
• Contribute to the integration of LLM-based reasoning into trading workflows (e.g., factor discovery, market regime detection).
• Collaborate with quants to translate trading hypotheses into agentic workflows, ensuring they are quantifiable and testable.
• Optimize system performance across real-time data streams, distributed backtesting, and live trading engines.
• Participate in code reviews, testing, and debugging for robustness of AI-driven agents.
• Document designs, experiments, and learnings to accelerate iteration cycles.

Skills

Python

C++

LangChain

Reinforcement learning

Multi-agent systems

Education

Bachelor's degree in CS/AI/DS

Tools

NumPy

Pandas

PyTorch

TensorFlow

Airflow

Ray

Job description

Role Overview

We are seeking a Junior AI Engineer to join our multi-agent systems team. You will be responsible for designing, implementing, and maintaining AI-driven agent workflows that support our quantitative research, backtesting engines, and live trading infrastructure. This is a hands‑on role where you’ll work closely with senior engineers and quant researchers to turn experimental ideas into production‑ready agents that generate measurable alpha.

Key Responsibilities

• Develop and maintain multi-agent AI pipelines for feature generation, factor evaluation, and strategy testing.
• Implement autonomous agent behaviors for data ingestion, strategy induction, and trade log analysis.
• Contribute to the integration of LLM-based reasoning into trading workflows (e.g., factor discovery, market regime detection).
• Collaborate with quants to translate trading hypotheses into agentic workflows, ensuring they are quantifiable and testable.
• Optimize system performance across real‑time data streams, distributed backtesting, and live trading engines.
• Participate in code reviews, testing, and debugging to ensure robustness and reliability of AI-driven agents.
• Document designs, experiments, and learnings to accelerate iteration cycles.

Requirements

• Bachelor’s degree in Computer Science, AI/ML, Data Science, or a related field.
• Strong proficiency in Python or C++ (bonus: both).
• Familiarity with agentic AI frameworks (LangChain, AutoGen, CrewAI, etc.) or strong willingness to learn.
• Knowledge of machine learning concepts, reinforcement learning, or multi‑agent systems.
• Exposure to quantitative finance, trading systems, or market data processing is a plus.
• Ability to write clean, modular, and well‑documented code.
• Strong problem‑solving mindset and bias toward rapid experimentation.

Nice‑to‑Haves

• Experience with LLMs, prompt engineering, or vector databases (e.g., Pinecone, Postgres w/ pgvector).
• Knowledge of numerical computing (NumPy, pandas, PyTorch, TensorFlow).
• Familiarity with distributed systems and DAG orchestration tools (Airflow, Prefect, Ray).
• Understanding of financial market structure, small‑cap equities, or alternative asset classes (crypto, options, futures).

What We Offer

• Opportunity to work at the frontier of AI x Quant trading, building systems that redefine what’s possible.
• Fast‑paced, iterative environment where ideas move quickly from prototype to production.
• Mentorship from seasoned quant traders and AI engineers.
• Competitive compensation and performance‑based upside.
• Exposure to multi‑asset, multi‑strategy trading pipelines and real‑world alpha generation.