The AI Platform Specialist will be a key member of the Data Science Platforms and Products team within UOB's Enterprise AI (EAI) center of excellence. This role focuses on managing and evolving the enterprise AI platform, enabling advanced Generative AI (GenAI) and Agentic AI solutions across the bank. The role requires a blend of AI engineering, data science expertise, and operational excellence to translate business requirements into scalable AI solutions.
Key Responsibilities:
AI Platform Management
- Serve as the functional SME for the AI platform, defining requirements and guiding platform design choices to align with business objectives.
- Partner with technology teams and vendors to deliver platform enhancements and improvements.
- Define and implement platform operating models, ensuring governance, security, compliance, and operational efficiency.
- Monitor platform utilization, performance, and cost efficiency, providing actionable insights for optimization.
Solution Enablement & Deployment
- Support onboarding of AI, GenAI, and Agentic AI use cases onto the platform in collaboration with data scientists, engineers, and business stakeholders.
- Design and develop reusable libraries, frameworks, and utility tools to accelerate solution development and deployment.
- Drive best practices for AI platform usage, user training, and organizational adoption.
Innovation & Continuous Improvement
- Stay updated with industry trends, emerging AI technologies, and best practices.
- Recommend enhancements to platform architecture and AI capabilities to maintain cutting-edge performance.
Key Requirements:
- Bachelor's or advanced degree in Computer Science, Data Science, Software Engineering, or related field.
- Minimum 8 years of experience in AI engineering or related roles, with hands-on experience deploying AI/GenAI/Agentic AI solutions in production.
- Strong knowledge of AI/GenAI/Agentic AI technologies including LLMs, context engineering, RAG, agent frameworks, and memory management.
- Hands-on experience with data management technologies including Hadoop, Spark, ETL, relational/non-relational databases, vector databases, and knowledge graphs.
- Familiarity with cloud platforms (Azure, AWS, GCP), containerization (Docker, Kubernetes), API management, DevOps, and CI/CD practices.
- Proficiency in Python; knowledge of Java or Scala is a plus.
- Experience in banking or financial services is preferred.
