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1-4 Years
SGD 5,000 - 10,000 per month
Early Applicant
  • Posted 23 hours ago
  • Be among the first 10 applicants

Job Description

MS Capital is a private fund management company with a strong founding team with long-accumulated experience in strategy modelling, trading system and platform development. Using advanced artificial intelligence technology as the cornerstone, and enforcing strict investment management, the company's investment fund has gained sustained and stable returns.

We are looking for a highly skilled AI Engineer with expertise in with deep technical expertise and practical understanding of agentic systems, LLM integration, and applied AI workflows in financial environments. The candidate will play a key role in designing and deploying intelligent agent applications that support trading, research, and operational automation across the hedge fund platform.

Key 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. Experiment with multi-agent architectures, RAG pipelines, and skill development frameworks.
  • Apply emerging AI technologies to enhance trading infrastructure and research processes.
  • Collaborate with quantitative researchers and data scientists to integrate multi-scenario financial AI models into research and trading platforms

Required Qualifications:

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

Interested applicants please apply and/or send your resume to [Confidential Information]

More Info

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Key Skills

agentic systems

applied AI workflows

AI libraries

AI-assisted development tools

LLM integration

RAG multi-agent frameworks

workflow orchestration systems

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