AVP/VP, AI Engineer, Data Management Office

The Japan Research Institute, Limited (Singapore Branch); Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Sumitomo Mitsui Banking Corporation is hiring for an AI/ML Engineer to design and implement agentic AI workflows with robust evaluation and governance in a Singapore-based role.

Requirements include 3+ years in AI/ML, Python proficiency, and experience with LLM architectures, API integration, and orchestration. Familiarity with Azure, PyTorch, TensorFlow and MLflow is a plus. Collaboration with risk, data science and engineering teams is essential.

Qualifications

• Minimum 3 years of AI/ML engineering experience.
• Strong understanding of multi-step reasoning and orchestration.
• Hands-on API integration and workflow automation experience.
• Proficiency with Python and ML frameworks.

Responsibilities

• Design, build and validate agentic AI workflows with multi-step reasoning.
• Integrate APIs, tools and connectors for agent operations.
• Develop evaluation pipelines for LLMs and agentic systems.
• Assess retrieval and vector databases, memory and reliability.
• Collaborate with data science, risk and engineering teams on safe AI deployment.
• Promote Responsible AI practices and governance.

Skills

Machine Learning

LLM Architectures

Python

API Integration

Workflow Orchestration

Model Evaluation

Observability & Debugging

Azure

Tools

Power Automate

Power Apps

SharePoint

MLflow

PyTorch

TensorFlow

Keras

scikit-learn

MLlib

Job description

Headquartered in Tokyo, Sumitomo Mitsui Banking Corporation (SMBC) is a leading global financial institution and a core member of Sumitomo Mitsui Financial Group (SMBC Group). Built upon our rich Japanese heritage since 1876, we put our customers first and provide seamless access to, from and within the Asia Pacific region. SMBC is one of the largest Japanese banks by assets and maintain strong credit ratings across our global integrated network. We work closely as one SMBC Group to offer personal, corporate and investment banking services to meet the needs of our customers.

With sustainability embedded within our strategy and operations, we are committed to creating a society in which today’s generation can enjoy economic prosperity and well-being, and pass it on to future generations.

Location

Singapore

Responsibilities

• Design, build and validate agentic AI workflows, including multi ‑ step reasoning and tool ‑ use orchestration.
• Integrate APIs, external tools, plugins and system connectors required for agent operations.
• Develop and execute evaluation approaches for LLMs and agentic systems, including scenario tests, benchmarks and automated pipelines.
• Assess retrieval components, vector databases, memory systems and workflow reliability.
• Apply Responsible AI principles and regulatory expectations to model behaviour, documentation and control standards.
• Partner with data science, engineering, architecture and risk teams to ensure safe and compliant AI deployment.
• Collaborate with other departments’ data scientists to understand modelling intent, technical assumptions and workflow logic.
• Contribute to AI/ML proof ‑ of ‑ concept (POC) initiatives to strengthen evaluation practices and support innovation.

Requirements

• Strong understanding of machine learning and LLM architectures, including components used in agentic AI systems.
• Minimum 3 years of relevant experience in AI/ML engineering, model development, model evaluation, or related technical roles.
• Knowledge of multi ‑ step reasoning, planning loops, workflow orchestration and tool ‑ use frameworks.
• Experience evaluating LLMs, agents and AI systems through scenario ‑ based testing, automated evaluations and diagnostic tracing.
• Ability to assess robustness, stability, drift, failure recovery behaviours and unintended model actions.
• Hands ‑ on experience with API integration, workflow automation and inter ‑ system tool ‑ use; familiarity with Power Automate, Power Apps, Sharepoint is a plus.
• Understanding of AI governance frameworks, lifecycle controls, Responsible AI principles and regulatory expectations.
• Strong prompting, debugging, observability and tracing skills to diagnose complex multi ‑ turn agent behaviours.
• Ability to collaborate across technical, risk, governance and business teams effectively.
• Proficiency in Python (especially pyspark, MLlib), Hadoop stack and modern AI/ML frameworks such as PyTorch, TensorFlow, Keras, scikit-learn; familiarity with ML lifecycle framework/tool such as MLflow; familiarity with RAG, vector databases, retrieval systems and orchestration libraries is a plus.
• Familiarity with Copilot Studio is a huge plus.
• Strong familiarity with Microsoft Azure, Azure Databricks and Microsoft Purview is a huge plus.