GenAI Engineer — Agentic AI for Banking Innovation

UOB; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

1011 United Overseas Bank Ltd is seeking a senior AI/ML operations leader to drive governance, roadmaps, and incident triage for agentic applications. You will collaborate across tech and business teams to implement responsible AI practices while optimizing prompts and model workflows.

The role requires deep data science knowledge, hands-on experience with large language models, and ability to translate complex concepts for non-technical stakeholders. Banking domain experience is a plus.

Qualifications

• Strong data science fundamentals: experimental design, measurement, error analysis, statistics.
• Hands-on Python experience for prototyping and production-grade experimentation.
• Experience with LLM and agentic AI systems: fine-tuning, prompt optimization, evaluation frameworks.
• Applied NLP skills: embeddings, retrieval methods, classification/extraction, calibration, reliability concepts.
• Responsible AI: bias testing, privacy leakage checks, audit artifacts.

Responsibilities

• Drive operational excellence and governance for agentic applications.
• Define roadmaps, evaluation processes, and compliance in agentic operations.
• Lead issue triage and resolution for agent-related incidents and improvements.
• Monitor performance metrics and optimize prompts, pipelines, and costs.
• Develop SOPs, FAQs, and user guides for agentic workflows.

Skills

Performance Monitoring

Process Improvement

Service Lifecycle Management

Education

Bachelor’s degree in Data Science, Statistics, Computer Science, Information Systems, or related field

Tools

Claude Sonnet 3.5

GPT-class models

Job description

1011 United Overseas Bank Ltd is seeking a senior AI/ML operations leader to drive governance, roadmaps, and incident triage for agentic applications. You will collaborate across tech and business teams to implement responsible AI practices while optimizing prompts and model workflows.

The role requires deep data science knowledge, hands-on experience with large language models, and ability to translate complex concepts for non-technical stakeholders. Banking domain experience is a plus.