AI and Data Governance Consultant (Lead)

AI governance advisory

• Assess a client's current AI estate: what models are in use, who approved them, what data they touch, and where the gaps between stated policy and actual practice sit.
• Design AI governance operating models that work inside the client's organisation, covering model inventories, risk classification, approval gates, human oversight, monitoring, and incident handling.
• Lead readiness and gap assessments against ISO/IEC 42001, the EU AI Act, the NIST AI Risk Management Framework, and Thai regulatory expectations, then turn the findings into a sequenced remediation plan the client can actually fund.
• Run AI risk assessments on specific systems, including generative and LLM-based applications, covering bias and fairness, explainability, data provenance, third-party model dependencies, and failure modes that matter to the business.
• Write the artefacts clients are asked to produce: AI policy, acceptable use standards, model documentation templates, risk registers, and committee terms of reference.
• Prepare and support clients through certification audits and scrutiny from regulators or their own enterprise customers.

Data governance

• Establish data governance foundations where AI governance depends on them: ownership and stewardship, classification, lineage, retention, and quality standards.
• Connect governance requirements to how data actuall