AVP for AI Development

Job Description & Requirements

Position Overview

We are seeking an experienced Industry AI Product Assistant Vice President to lead the strategy, development, and commercialization of next-generation AI-driven Industrial solutions, particularly for semiconductor and related manufacturing.

This executive role will be responsible for defining AI product strategy, overseeing product development, and leading customer delivery programs for semiconductor manufacturers in Singapore and across Asia. The position also plays a critical role in technical pre-sales, customer solution design, and strategic industry engagement.

The successful candidate will bring deep expertise in manufacturing operation, industrial data platforms, AI-driven analytics, and smart factory transformation. The role requires close collaboration with product engineering teams, sales teams, and global industry customers to deliver high-impact AI solutions that improve equipment reliability, yield and operational efficiency.

Key Responsibilities

1. AI Product Strategy & Portfolio Leadership

• Define and execute the AI product strategy for manufacturing industry solutions.
• Develop a portfolio of AI-driven smart manufacturing products, including:
• Equipment Predictive Maintenance Fault Detection & Classification (FDC) Process anomaly detection Yield improvement analytics Intelligent alarm and deviation management Manufacturing data integration platforms
• Identify industry trends and emerging technologies to drive continuous innovation in industrial AI products.
• Build scalable product frameworks that can be deployed across multiple semiconductor fabs.

2. Product Development &Technology Leadership

Lead cross-functional teams to design and develop AI products integrating:

• machine learning
• industrial data platforms
• advanced analytics
• digital twins
• knowledge graph technologies
• Define technical architecture for industrial AI platforms, ensuring scalability, security, and real-time analytics capability.
• Work closely with engineering teams to implement robust data pipelines and MLOps practices.
• Establish product lifecycle management from concept → prototype → industrial deployment → continuous optimization.

3. Customer Delivery Leadership

Lead the execution of AI-driven transformation programs for target industry customers. Manage customer engagements including:

• requirements discovery
• solution design
• implementation planning
• deployment and value realization

Ensure delivery of measurable business outcomes such as:

• improved equipment uptime
• yield improvement
• process stability
• reduced manufacturing downtime.

4. Technical Pre-Sales & Customer Engagement

• Support the sales organization in solution architecture, proposal development, and technical presentations.
• Engage customers through workshops and consulting sessions to identify high-value AI use cases.
• Lead product demonstrations and technical discussions with fab leadership teams.
• Represent the company at industry conferences, technology forums, and strategic customer meetings.

5. Industry Innovation & Thought Leadership

• Monitor the evolution of AI technologies and semiconductor manufacturing trends.
• Build strategic partnerships with AI technology providers and ecosystem partners.
• Position the company as a leader in AI-driven semiconductor manufacturing solutions.

Required Qualifications

Education

Bachelor’s or Master’s degree in:

• Computer Science
• Data Science
• Information Technology
• AI Engineering
• Industrial Engineering

Expected Professional Experience

Industry Experience

• 15+ years of experience in Software Engineering, Industrial AI, or Advanced Industry technologies.
• Strong understanding of industry operations including equipment automation and manufacturing systems.
• Experience working with major industry customer, particularly semiconductor manufacturers.

Industrial Data Engineering

Demonstrated experience in designing and implementing industrial data platforms including:

• Manufacturing data pipelines and ETL frameworks
• Data lake / data warehouse architectures
• Time-series data analytics for equipment and process monitoring
• Real-time streaming data processing
• Data governance and industrial data management frameworks

AI & Advanced Analytics Applications

Hands-on or leadership experience delivering AI solutions in manufacturing environments including:

• Equipment Predictive Maintenance
• Fault Detection and Classification (FDC)
• Process anomaly detection
• Yield prediction and yield optimization
• Root cause analysis automation
• Manufacturing performance analytics
• Intelligent alarm management systems

Manufacturing Systems Integration

Strong familiarity with manufacturing systems integration such as:

• Manufacturing Execution System (MES)
• Equipment Automation Program (EAP)
• CIM systems and factory automation platforms
• Equipment communication protocols such as SECS/GEM

Data Insight & Industrial Intelligence

Experience applying advanced analytics techniques including:

• Process mining
• Multivariate data analysis
• Statistical Process Control (SPC)
• Knowledge graph-based manufacturing intelligence
• Operational intelligence dashboards and visualization platforms

AI Platform & Engineering Experience

• Familiarity with AI/ML development frameworks and tools.
• Experience implementing MLOps pipelines and model lifecycle management.
• Understanding of deploying AI solutions in high-availability manufacturing environments.

Key Competencies

Strategic Leadership

• Ability to define product vision and long-term AI strategy.
• Strong commercial awareness and product management expertise.

Industry Domain Expertise

• Deep understanding of Industry operation processes and factory systems.
• Ability to translate fab operational challenges into AI product opportunities.

Technical & Architectural Thinking

• Strong understanding of data architecture, AI systems, and industrial software platforms.

Customer Engagement

• Excellent ability to communicate with customer executives and technical teams.
• Experience leading complex customer transformation projects.

Cross-Functional Leadership

• Ability to lead multidisciplinary teams including software engineers, data scientists, and domain experts.

Innovation Mindset

• Passion for applying AI technologies to solve real-world manufacturing challenges.