AVP, AI Engineer - Global Financial Market Technology

About the role

DBS is hiring an AVP AI Engineer within its Group Technology team, which manages the majority of the bank's operational processes and delivers banking services across multiple channels. The role focuses on building AI solutions for Global Financial Markets, working from DBS Asia Central.

Key responsibilities

• Design and develop Agentic AI, Generative AI and RAG solutions, including AI agents, orchestration, tool calling, prompt engineering, memory, reflection and evaluation.
• Build ML and data science models for client propensity, recommendations, classification, ranking, behavioural analytics and next-best-action use cases.
• Analyse structured and unstructured data, perform data exploration, feature engineering, model evaluation and performance monitoring.
• Develop scalable, production-ready AI services and APIs and integrate them with enterprise systems and data sources.
• Build reusable AI components and frameworks supporting multiple business use cases.
• Implement monitoring, observability and evaluation, optimising AI solutions for scalability, performance, accuracy and cost.
• Partner with business stakeholders, product owners, data scientists and engineers to turn Global Financial Markets requirements into AI-powered solutions.

Required profile

• Hands-on experience in AI/ML engineering, data science or advanced analytics, including deploying ML/AI solutions into production.
• Mandatory generative AI experience covering RAG, vector search, LLM applications, Dify and agentic AI frameworks.
• Preferred experience in banking, financial services, capital markets or wealth management.
• Advantageous experience in recommendation/personalisation engines, search and retrieval, knowledge management, MLOps/LLMOps, AI governance and enterprise document repositories.

Required skills

• Strong proficiency in Python, SQL and REST APIs.
• ML frameworks such as Scikit-Learn, XGBoost/LightGBM, TensorFlow or PyTorch.
• Data pipelines, data transformation, feature engineering and data quality management.
• OpenShift (OCP), Docker, Kubernetes, CI/CD and Git.