Applied AI Engineer, Vice President, Institutional Securities Technology

Morgan Stanley Asia Limited; Hong Kong; On-site; HKD 2,000,000 - 4,000,000; Full time

Job summary

Applied AI Engineer, Vice President, Institutional Securities Technology at Morgan Stanley Asia Limited, leads GenAI initiatives and delivery across business and tech teams in Hong Kong. You will drive PoC-to-production, design scalable architectures, and ensure governance and security across AI platforms.

The role emphasizes hands-on engineering, collaboration with risk/compliance, and developing reusable components for enterprise AI applications in a fast-paced financial services environment.

Qualifications

• Bachelor's or Master's degree in Computer Science or related field.
• 5–10+ years of experience in software engineering or AI/ML.
• Hands-on experience with LLMs, APIs, and distributed systems.
• Programming skills (Python, Java, or similar).
• Experience delivering production-grade systems.
• Bachelor's or Master's degree in Computer Science or related field.

Responsibilities

• Partner with ISG business and technology teams to identify, prioritize, and deliver high-value GenAI use cases.
• Move use cases from PoC to production, ensuring scalability, robustness, and integration.
• Define and implement reusable architectures and engineering patterns.
• Ensure solutions meet performance and reliability requirements.
• Design and build solutions leveraging LLMs, agent frameworks, and orchestration tools.
• Integrate GenAI into internal platforms and applications.
• Collaborate with enterprise AI/ML platforms and contribute reusable components.
• Ensure compliance with security, data privacy, and regulatory requirements.
• Implement guardrails (validation, auditability, monitoring).
• Partner with risk and compliance teams on governance.
• Define KPIs and track business impact.
• Communicate outcomes to senior stakeholders.
• Optimize solutions for value delivery.
• Enable teams through best practices and training.
• Define AI-assisted development guidelines.
• Drive adoption of AI-enabled ways of working.

Skills

LLMs

APIs

Distributed systems

Python

Java

Production-grade systems

AI governance

Education

Bachelor's or Master's in Computer Science or related field

Tools

DevOps

LLM tooling

Job description

Applied AI Engineer, Vice President, Institutional Securities Technology

Key Responsibilities

• GenAI Use Case Delivery & Industrialization
  • Partner with ISG business and technology teams to identify, prioritize, and deliver high-value GenAI use cases.
  • Move use cases from PoC to production, ensuring scalability, robustness, and integration.
  • Define and implement reusable architectures and engineering patterns.
  • Ensure solutions meet performance and reliability requirements.
• Engineering & Platform Integration
  • Design and build solutions leveraging LLMs, agent frameworks, and orchestration tools.
  • Integrate GenAI into internal platforms and applications.
  • Collaborate with enterprise AI/ML platforms and contribute reusable components.
• Responsible AI, Risk & Controls
  • Ensure compliance with security, data privacy, and regulatory requirements.
  • Implement guardrails (validation, auditability, monitoring).
  • Partner with risk and compliance teams on governance.
• Business Value Realization
  • Define KPIs and track business impact.
  • Communicate outcomes to senior stakeholders.
  • Optimize solutions for value delivery.
• Engineering Enablement & Change Adoption
  • Enable teams through best practices and training.
  • Define AI-assisted development guidelines.
  • Drive adoption of AI-enabled ways of working.
• Qualifications
  • Bachelor's or Master's degree in Computer Science or related field.
  • 5-10+ years experience in software engineering or AI/ML.
  • Hands-on experience with LLMs, APIs, and distributed systems.
  • Programming skills (Python, Java, or similar).
  • Experience delivering production-grade systems.
  • Bachelor's or Master's degree in Computer Science or related field.

Preferred Qualifications

• Experience in financial services or trading technology (preferable but not essential)
• Familiarity with RAG, vector databases, and prompt engineering.
• Understanding of AI governance and regulatory expectations.
• Experience with developer productivity tools and AI coding solutions.
• Exposure to data engineering pipelines.

Key Competencies

• Business-driven mindset
• Strong execution focus
• Stakeholder engagement
• Structured problem-solving
• Collaboration
• Adaptability

Since our founding in 1935, Morgan Stanley has consistently delivered first-class business in a first-class way. Underpinning all that we do are five core values.

Since our founding in 1935, Morgan Stanley has consistently delivered first-class business in a first-class way. Underpinning all that we do are five core values.