First VP, GenAI Engineer/Scientist Lead, Innovation Group

This role leads the operational adoption and governance of agentic applications across UOB. It defines roadmaps and evaluation processes, maintains agent-based solutions, and works with business, technology, and innovation teams to deliver secure, efficient, compliant operations. The position is on-site in Central Region (City Area), Singapore.

Responsibilities

• Improve agent performance and capabilities, and design, build, and roll out solutions to additional users. Manage agent onboarding, configuration, and retirement; monitor uptime, performance, and service-level agreements.
• Integrate agent workflows with incident, problem, and change management. Maintain logging, audit trails, reporting, SOPs, FAQs, and user guides. Use root cause analysis, automation, and performance optimization to improve operations.
• Apply frameworks to evaluate agent performance, reliability, and compliance. Lead incident triage and resolution, working with cross-functional teams on corrective actions.
• Design and refine prompts, system messages, few-shot examples, and pipelines for relevance, accuracy, and cost efficiency. Monitor latency, token usage, and output quality; update roadmaps and prompts in response to regulatory, policy, or business changes while following ethical guidelines.

Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Information Systems, or a related field; 15+ years of hands-on experience designing, building, and operationalizing end-to-end AI/ML systems, from data preparation and model development through deployment and post-production monitoring.
• A minimum of 1–2 years of dedicated generative AI and large language model project experience. Hands-on experience with prompt design, output tuning, and integration of models such as Claude Sonnet 3.5 or GPT-class models into end-user applications.
• Strong data science fundamentals and Python experience; experience with LLM and agentic AI systems, fine-tuning, RAG, prompt optimization, evaluation, applied NLP, and responsible AI practices. Familiarity with AI agent evaluation and the ability to explain technical concepts to non-technical stakeholders are required. Banking or financial services experience is a plus.