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 actually moves in the client's platforms, working with our data engineers rather than producing documents that sit apart from the systems.
- Align governance design with PDPA and, where relevant, GDPR, in partnership with our privacy and legal function.
Client leadership and business development
- Own delivery on your engagements end to end: scope, plan, workshops, deliverables, and the final read-out to the executive sponsor.
- Build trust with senior stakeholders and hold a position when the commercially convenient answer is not the correct one.
- Work with our commercial team on scoping calls, proposals, and pricing, and lead the technical argument in pitches.
- Develop repeatable service offerings, assessment methods, and templates so the practice does not restart from a blank page on every engagement.
- Represent Data Wow externally through client briefings, industry events, and written material on AI governance in the Thai market.
- Coach consultants and engineers on the team so governance thinking spreads beyond you.
Requirements
Required
- 5+ years in consulting, risk, compliance, data governance, or a related advisory function, including at least 2 years focused on AI, data, or technology governance.
- Direct experience leading client engagements: setting scope, managing stakeholders, and presenting to executives without a partner in the room.
- Working command of at least one AI governance framework such as ISO/IEC 42001, the EU AI Act, or the NIST AI RMF, applied in practice rather than read about.
- Solid grounding in data governance disciplines: ownership models, classification, lineage, quality, and retention.
- Enough technical fluency to hold a credible conversation with data scientists and engineers about how models are trained, deployed, and monitored. You do not need to build them.
- Familiarity with PDPA and how privacy obligations interact with AI systems.
- Clear written and spoken English and Thai. Much of this work is persuasion in writing.
- Comfort with ambiguity. Regulation in this area is still forming, and clients will ask you questions that do not yet have settled answers.
Nice to have
- Experience in a Big Four practice, a boutique consultancy, or an in-house governance function at a regulated enterprise.
- Certifications such as ISO/IEC 42001 Lead Auditor or Lead Implementer, ISO 27001 Lead Auditor, CIPP/E, CIPM, or CDMP.
- Sector depth in financial services, healthcare, or energy, where regulatory pressure on AI is arriving first.
- Hands-on exposure to MLOps tooling, model monitoring, or LLM evaluation.
- A track record in business development, including proposals you wrote that were won.
- Published writing or speaking on AI governance, data ethics, or privacy.
Benefits
- Hybrid Working options with Flexible Working Hours.
- Your Choice of Gear: Mac or Windows? You pick your preferred work equipment.
- Comprehensive Group Health Insurance.
- Monthly Grab Transportation credits.
- Job-related training courses and certificate fee coverage.
- 10+ days of annual leave.
- Free snacks and drinks available at the office.