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OCBC (Singapore) is seeking an AI Validation Specialist (AVP) to validate critical AI solutions and support governance across the bank. You will conduct hands-on testing, design evaluation frameworks for GenAI, and document findings for risk management and executive review.
You will lead validation efforts, assess guardrails and tool-use permissions, and collaborate with Risk, Technology, and Audit teams to ensure responsible AI deployment.
As Singapore’s longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires.
Today, we’re on a journey of transformation. Leveraging technology and creativity to become a future‑ready learning organisation. But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia’s leading financial services partner for a sustainable future.
We invite you to build the bank of the future. Innovate the way we deliver financial services. Work in friendly, supportive teams. Build lasting value in your community. Help people grow their assets, business, and investments. Take your learning as far as you can. Or simply enjoy a vibrant, future‑ready career.
Your Opportunity Starts Here.
Reporting to the Group Data Office, Responsible AI Lead, you will help validate the bank’s most critical AI solutions, ensuring they are fit for purpose and comply with AI governance standards. The role conducts hands‑on testing, identifies risks and limitations, and provides recommendations to support the safe and responsible use of AI across the bank.
Conduct independent validation of traditional machine learning models across the full model lifecycle.
Design the validation frameworks, methodologies and testing approaches for GenAI solutions and agentic AI systems.
Review and challenge model evaluation results, including assessments of performance (e.g. groundedness, factual accuracy, retrieval quality, relevance, and instruction adherence), and evaluate the reliability of LLM-as-a-Judge methodologies through calibration against human‑labelled benchmarks.
Perform structured testing of AI guardrails and assess agentic AI systems for appropriate tool‑use permissions, action reversibility, and human‑in‑the‑loop controls.
Document validation findings, identified limitations, risks, and recommendations and support the communication of validation outcomes.
Contribute to the development and enhancement of the bank’s AI validation methodologies, evidence standards, and reusable testing assets.
Provide technical expertise to stakeholders across Risk, Technology, Internal Audit, and business functions.
Monitor evolving AI technologies, regulatory expectations, and industry best practices, and incorporate relevant developments into validation standards and approaches.
Advanced degree in Artificial Intelligence, Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related AI Governance discipline.
5–8 years’ experience in model validation and testing within a bank or another regulated environment, with the ability to apply traditional model risk management principles to emerging AI use cases, including Generative AI and agentic AI systems.
Ability to critically assess and challenge complex AI systems, identify risks, and recommend effective controls.
Strong understanding of AI lifecycle management, bias and fairness, explainability, controls and guardrails and monitoring concepts.
Strong written and verbal communication skills, with the ability to produce decision‑ready and regulatory‑grade documentation and communicate technical and governance concepts to senior management and non‑technical stakeholders.
Hands‑on experience designing and executing GenAI evaluation methodologies and testing frameworks.
Hands‑on experience with ML/GenAI frameworks and cloud‑based AI services.
Familiarity with MAS and other regulatory frameworks covering AI risk management, data governance, technology risk, information security, and third‑party risk management.
Experience contributing to the design and implementation of model management, governance, or risk management platforms.
Exposure to industry forums, regulatory working groups, or governance committees related to AI.
Competitive base salary. A suite of holistic, flexible benefits to suit every lifestyle. Community initiatives. Industry‑leading learning and professional development opportunities. Your wellbeing, growth and aspirations are every bit as cared for as the needs of our customers.