Job Description: AI Scientist – Agentic AI for Financial Services

About Us

At A*STAR Institute of High Performance Computing (A*STAR IHPC), our team conducts advanced AI research to solve real-world challenges in financial services. We focus on developing agentic AI systems, large language models (LLMs), and foundation models that enable complex reasoning, and automation across financial workflows.

Our work bridges cutting-edge AI research and practical financial applications, including intelligent document analysis, regulatory compliance, risk reasoning, and decision support. We collaborate closely with fintech companies and financial institutions to translate research innovations into deployable systems.

We are seeking AI Scientists to join our team. In this role, you will design and development of agent-based AI systems that combine LLM reasoning, and structured workflows to address complex financial problems, while ensuring transparency, and trustworthiness.

Requirements

Must-Have Qualifications

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or related field
• Research and hands-on experience with Agentic AI
• Deep expertise in large language models (LLMs) and foundation models
• Strong publication record in top-tier AI/ML conferences or high-impact journals

Strong-Plus Qualifications

• Background in economics, finance, or financial systems (e.g., banking, risk, compliance)
• Solid understanding of financial services domains, data, or regulatory environments
• Experience designing evaluation frameworks for reasoning quality, reliability, and robustness of AI systems
• Publications, patents, or impactful contributions in AI for financial services

Key Responsibilities

• Lead the design and implementation of agentic AI systems for financial services applications
• Investigate and advance methods to improve reasoning accuracy, controllability, explainability, and safety in agent-based architectures
• Publish original research in top-tier AI and machine learning venues (e.g., ACL, EMNLP, NeurIPS, ICML, ICLR, AAAI)
• Collaborate with cross-functional internal teams and industry partners to align agentic AI solutions with real-world financial constraints and requirements