Banking AI Architect: GenAI, LLM & Data Governance

Infosys-Singapore-; Singapore; On-site; SGD 180,000 - 340,000; Full time

Job summary

Infosys-Singapore- seeks a visionary AI Architect to lead design, development and deployment of AI solutions across FS banking operations. You’ll shape AI strategy, ensure scalable and secure integration, and oversee governance and risk management.

Role requires hands-on GenAI/LLM work, data pipelines, and model finetuning, with cross-functional collaboration and mentorship of AI engineers and data scientists. Strong cloud and regulatory knowledge essential.

Qualifications

• Bachelor's or Master's in Computer Science, Data Science, AI or related field.
• Proven experience in AI/ML solution architecture, preferably in financial services.
• Strong knowledge of cloud platforms (Azure, Databricks) and data engineering.
• Familiarity with regulatory frameworks and ethical AI practices in banking.
• Experience with GenAI Observability, Traceability and Explainability tools.

Responsibilities

• Define and implement the bank's AI architecture and roadmap.
• Lead end-to-end design for GenAI/LLM and AI/ML models, incl. data pipelines and training.
• Collaborate with data science, engineering and business units to identify use cases.
• Ensure AI systems comply with regulatory requirements and data governance policies.
• Evaluate and integrate emerging AI technologies, platforms and tools.
• Provide technical leadership and mentorship to AI engineers and data scientists.

Skills

AI/ML architecture

GenAI/LLM design

Cloud platforms

Regulatory compliance & data govern

Stakeholder management

Team mentorship

Education

Bachelor's or Master's in Computer Science/Data Science/AI or related field

Tools

Azure

Databricks

OpenAI

Anthropic models

Job description

Infosys-Singapore- seeks a visionary AI Architect to lead design, development and deployment of AI solutions across FS banking operations. You’ll shape AI strategy, ensure scalable and secure integration, and oversee governance and risk management.

Role requires hands-on GenAI/LLM work, data pipelines, and model finetuning, with cross-functional collaboration and mentorship of AI engineers and data scientists. Strong cloud and regulatory knowledge essential.