AI Agent Engineer for Quant Finance & Workflow Automation

MS Capital Singapore

Singapore

On-site

SGD 100,000 - 160,000

Full time

40 hours ago
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Job summary

MS Capital Singapore is building an AI Agent Team focused on AI-driven workflows in quantitative finance. You will develop AI agents for financial data analysis, automate research, and optimize trading workflows, collaborating with portfolio managers, researchers, and developers.

No traditional finance background is required; curiosity, structured thinking, and quick learning are valued. You’ll work on multi-agent architectures and state-of-the-art tools to advance AI-enabled finance research.

Qualifications

  • Degree in Computer Science, Engineering, Machine Learning or related field.
  • Strong proficiency in Python programming and familiarity with AI libraries.
  • Experience with RAG, multi-agent frameworks, or workflow orchestration systems.
  • Hands-on experience with AI-assisted development tools such as Claude Code, Codex, Cursor.

Responsibilities

  • Build and maintain AI agents for financial data analysis, research automation, and workflow optimization.
  • Explore AI-driven workflows and agent-based systems in quantitative finance, including multi-agent architectures and RAG pipelines.
  • Apply AI technologies to enhance trading infrastructure and research processes.
  • Collaborate with researchers and data scientists to integrate AI models into research and trading platforms.

Skills

Python
AI libraries
RAG
Multi-agent
Workflow orchestration

Education

Computer Science / Engineering / ML

Tools

Claude Code
Codex
Cursor

Job description

MS Capital Singapore is building an AI Agent Team focused on AI-driven workflows in quantitative finance. You will develop AI agents for financial data analysis, automate research, and optimize trading workflows, collaborating with portfolio managers, researchers, and developers.

No traditional finance background is required; curiosity, structured thinking, and quick learning are valued. You’ll work on multi-agent architectures and state-of-the-art tools to advance AI-enabled finance research.

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