Lead AI Engineer

Role Overview:

We are seeking a highly experienced Lead AI Engineer with a strong background in the banking and financial services sector. The ideal candidate will bridge the gap between advanced AI technologies (GenAI, LLMs, RAG) and complex banking operations, driving legacy modernization and delivering compliant, high-ROI financial technology solutions.

Responsibilities

1. Banking AI Leadership: Lead the development, testing, and maintenance of large-scale AI applications tailored specifically for the banking domain (e.g., wealth management, risk assessment, fraud detection, and customer service automation).
2. Cross-Functional Collaboration: Partner closely with banking business units (Retail, Corporate, Risk, and Compliance) to deliver high-quality software solutions that align with the bank’s strategic and financial goals.
3. Financial Project Management: Manage end-to-end project delivery using Agile or Waterfall methodologies, handling stringent risk management, resource allocation, and stakeholder communication typical of highly regulated financial environments.
4. Banking Business Analysis: Act as a hybrid Business Analyst to elicit, analyze, and document complex banking requirements. Translate financial workflows into technical AI use cases on Customer Account Management, Treasury and Trade Finance, Payment and Settlement or Lending / Loan operations would be great values to the position
5. Regulatory Compliance & Security: Ensure all AI solutions, data pipelines, and system architectures strictly comply with banking industry standards, including HKMA regulations, Anti-Money Laundering (AML), Know Your Customer (KYC), and data privacy laws.
6. System Troubleshooting: Troubleshoot and debug mission-critical banking applications to ensure zero-downtime functionality and continuous regulatory compliance.
7. GenAI Modernization: Champion the adoption of the latest AI trends (LLMs, RAG, AI Agents) to drive GenAI-powered modernization of legacy banking systems.

Requirements

1. Domain Experience: Minimum 7 years of system development experience in large-scale AI or enterprise systems, with at least 5 years dedicated to banking, FinTech, or financial services.
2. Banking Knowledge: Deep understanding of banking operations, financial products, and regulatory frameworks (HKMA regulations, data security, and AML compliance) in system design and code development.
3. Project Management: Proven track record of managing complex IT projects within financial institutions using Agile/Scrum or Waterfall, utilizing tools like JIRA, Confluence, or MS Project.
4. Business Analysis: Proven ability to conduct requirement workshops with financial stakeholders, perform gap analysis, model banking business processes, and write detailed BRD/FRD and user stories.
5. AI & Machine Learning: Proficient in core AI/ML concepts and algorithms. Familiar with ML/DL frameworks (TensorFlow, PyTorch) and enterprise deployment of LLM models (DeepSeek, Gemini, Qwen, etc.).
6. Advanced AI Integration: Strong hands-on experience with Prompt Engineering, RAG frameworks, and building AI Agents. Capable of securely integrating AI capabilities into existing, highly-regulated banking applications or services.
7. Programming & Architecture: Strong programming background with proficiency in Python and Java (standard enterprise banking stack).
8. Cloud Infrastructure: Familiar with cloud platforms such as AWS or AliCloud, particularly in deploying secure, compliant architectures for financial data.
9. Legacy Modernization: Proven project experience in banking Legacy Modernization (e.g., migrating or augmenting legacy core banking systems) leveraging Generative AI or Spec Coding is a strong plus.
10. Language Skills: Excellent ability to read and write in English. Ability to communicate fluently in Cantonese is a strong plus for liaising with local stakeholders.