I. RANGE OF DUTIES:

1. Summary:

The AI Architect / Digital Lead is the delivery and technical execution arm of the company’s AI and digital transformation roadmap, reporting to the Head of Digital & Transformation. The role owns architecture and hands-on delivery across plant-floor, supply chain, and enterprise initiatives, and leads a specialist team that is expected to grow as the AI/digital portfolio expands.

Microsoft’s ecosystem (Copilot Studio, Power Platform, Azure AI, Dynamics 365, SharePoint, Power BI) is the company’s approved default toolkit; anything outside it requires Governance Committee approval.

This position need to ensure AI tools are deployed safely, integrated cleanly with core systems, and adopted by the people who use them every day.

2. Main Responsibilities

AI Tool Implementation & Management

• Lead AI and automated-workflow projects across plant operations, supply chain, and enterprise functions, sequencing which domain is resourced first and extending into new domains as the specialist team grows.
• Decide which AI and automation tools fit each use case, keeping the team within Microsoft’s ecosystem (Copilot Studio, Power Automate, Power Apps) as the company’s approved default toolkit.
• Ensure the team builds and maintains the automated workflows and low-code applications that streamline cross-departmental tasks and digitize manual factory-floor processes.

System Integration & Data

• Own technical integration between core systems — MES, Dynamics 365, SharePoint, and PDM — ensuring smooth, reliable data flow.
• Direct the team’s work bridging plant-floor and OT data (PLC, SCADA, sensors) into the company’s data warehouse, in coordination with Automation Engineering.
• Oversee data remediation and cleaning so AI models operate on high-quality master data.

Reporting & Analytics

• Ensure the specialist team builds and maintains dashboards and analytics that give plant and business leadership consistent, trustworthy real-time visibility into integrated systems.
• Review the operational and AI-driven analytics the team produces, and turn the findings into recommendations the leaders can act on.

Compliance & Escalation

• Operate within AI policy, data-handling, and security standards set by the AI Governance Committee, escalating anything ambiguous rather than deciding it unilaterally.
• Flag AI use cases that touch personal or sensitive data to the Governance Committee early enough for review under Vietnam’s data protection requirements.
• Partner with IT/Security to implement system security and compliance requirements throughout every AI tool deployment.
• Bring forward a business case when a use case needs a tool outside the approved Microsoft toolkit, for the Governance Committee to evaluate and approve.

Technical Support & Collaboration

• Provide technical expertise to internal stakeholders on using AI tools to improve daily efficiency.
• Conduct technical training sessions for end users to drive adoption of deployed AI solutions.
• Partner with Automation Engineering and IT/Security to ensure new data connections and AI deployments do not disrupt live production systems.

3.Key partners:

Automation/Industrial Engineering (OT data access and plant-floor deployments); IT/Security (infrastructure and compliance); business unit stakeholders requesting AI/digital support.

II. FORMAL REQUIREMENTS:

1. Education:

- Required: Bachelor’s degree in Computer Science, Information Technology, or Data Science, or Engineering.

- Preferable: Specialized certifications in Microsoft Power Platform

2. Professional knowledge of:

• Deep, hands-on experience with Microsoft’s AI and automation ecosystem (Copilot Studio, Power Platform, Azure AI, Dynamics 365/SharePoint), used as the company’s approved default toolkit.
• Working familiarity with the broader AI and data-tooling landscape beyond Microsoft — for example, alternative LLM providers, specialized computer-vision or quality-inspection platforms, or OT/IoT analytics tools — enough to recognize when a use case needs a Governance Committee exception, without the authority to grant one.
• Working knowledge of manufacturing systems (MES, PDM) and how plant-floor/OT data differs from transactional IT data.
• Enough data architecture literacy to direct AI and data-pipeline work without needing to build every model personally.
• Ability to build a clear, concise business case for a tooling exception, for the Governance Committee to evaluate.

3. Knowledge of foreign languages: Fluent English (Oral and Written)

4. Other (e.g. competences):

• Strong logical mindset and technical problem-solving skills.
• Analytical Mindset
• Self-awareness and self-discipline.
• Self-planning and self-organizing.
• Ability to work independently on technical tasks

Leadership & Communication

• Ability to explain technical options and constraints clearly to non-technical managers and end users.
• Comfortable operating inside a governance body’s decisions rather than setting policy independently.
• Strong stakeholder management across plant operations, supply chain, and corporate functions.

5. Professional experience:

• Mandatory: 5+ years of experience in digital transformation, data/AI, or enterprise systems, ideally within a manufacturing environment.
• Preferable: Experience leading a small technical team and managing multiple concurrent initiatives.