Artificial Intelligence Engineer (AI Engineer Senior)

UST; Singapore; On-site; SGD 180,000 - 300,000; Full time

Job summary

UST is seeking an experienced AI Engineering leader to architect and deliver enterprise-grade AI products, copilots, intelligent agents, and decision-support solutions for global Investment & Wealth Management clients in Singapore.

You will design AI-powered solutions, lead architecture decisions, integrate LLMs with enterprise data, and mentor engineers while partnering with domain experts to translate business requirements into scalable outcomes.

Qualifications

• 7+ years of software engineering experience
• 3+ years of hands-on GenAI and AI Engineering experience
• Proven track record of delivering production-grade AI solutions at scale
• Expertise in AI Engineering, LLMs, Agent Frameworks, RAG, Python, and Cloud-Native Development
• Experience in Enterprise Software Architecture, Data Engineering & MLOps, API & System Integrations
• Knowledge of Security, IAM, and AI Governance
• Domain knowledge in Investment Operations, Portfolio Management Workflows, Trading & Fund Accounting Concepts

Responsibilities

• Design and build AI-powered solutions for investment operations and wealth management
• Develop Agentic AI, RAG architectures, knowledge retrieval systems, and workflow automation
• Lead AI application architecture, solution design, and technical decision-making
• Integrate LLMs with enterprise platforms, data sources, and business systems
• Implement AI observability, governance, evaluation, security, and monitoring capabilities
• Partner with domain SMEs to translate business requirements into scalable AI solutions
• Mentor AI engineers and support customer implementations and production deployments

Skills

GenAI

AI Engineering

LLMs

Agent Frameworks

RAG

Python

Cloud-Native Development

AI Governance

Agentic AI

AI products

Copilots

Enterprise Software Architecture

Data Engineering

MLOps

IAM

AI Deployments

Job description

Role Description

Join our AI Engineering team to architect and deliver enterprise-grade AI products, copilots, intelligent agents, and decision-support solutions for global Investment & Wealth Management clients.

Role Description

Join our AI Engineering team to architect and deliver enterprise-grade AI products, copilots, intelligent agents, and decision-support solutions for global Investment & Wealth Management clients.

What We're Looking For

• 7-10+ years of overall software engineering experience


• 3+ years of hands-on GenAI and AI Engineering experience


• Proven track record of delivering production-grade AI solutions at scale


• Expertise in AI Engineering, LLMs, Agent Frameworks, RAG, Python, and Cloud-Native Development

Strong Experience In

• Enterprise Software Architecture


• Data Engineering & MLOps


• API & System Integrations


• Security, IAM, and AI Governance


• Production-scale AI deployments

Domain Knowledge In

• Investment Operations


• Portfolio Management Workflows


• Trading & Fund Accounting Concepts

What You'll Do

• Design and build AI-powered solutions for investment operations and wealth management


• Develop Agentic AI, RAG architectures, knowledge retrieval systems, and workflow automation


• Lead AI application architecture, solution design, and technical decision-making


• Integrate LLMs with enterprise platforms, data sources, and business systems


• Implement AI observability, governance, evaluation, security, and monitoring capabilities


• Partner with domain SMEs to translate business requirements into scalable AI solutions


• Mentor AI engineers and support customer implementations and production deployments

Why Join Us?

• Work and build cutting-edge AI solutions with the global clients.


• Lead innovation in GenAI, Agentic AI, Copilots, and Enterprise AI Platforms.


• Mentor high-performing engineering teams and shape AI transformation initiatives

Skills

GenAI, AI Engineering, LLMs, Agent Frameworks, RAG, Python, Cloud-Native Development, AI Governance, Agentic AI, AI products, copilots, Enterprise Software Architecture, Data Engineering, MLOps, IAM, AI Governance, AI deployments