Head of Applications Development – ERP, MES & AI Systems

TDCONNEX EASTERN PTE. LTD.; Singapore; On-site; SGD 150,000 - 200,000; Full time

Job summary

A leading company in manufacturing is seeking a strategic Head of Applications Development to drive digital transformation and smart manufacturing initiatives. The role involves overseeing application architecture, integrating AI, and leading a cross-functional team to enhance operational efficiency across global sites.

Qualifications

• 15+ years in software development and architecture.
• 5+ years in leadership roles.
• Deep expertise in Java, Python, and AI integration.

Responsibilities

• Lead application development strategies for smart manufacturing.
• Oversee integration of AI models and ERP systems.
• Manage cross-functional teams and ensure operational excellence.

Skills

Java

Python

J2EE

SpringBoot

JavaScript

ReactJS

AI/ML

ERP/MES integration

IoT platforms

CI/CD

Containerization

Cloud migrations

Distributed systems

Education

Master’s degree in Computer Science

Tools

AWS

Docker

Kubernetes

Job description

We are seeking an experienced and strategic Head of Applications Development to lead the architecture, development, and lifecycle management of enterprise applications across our global manufacturing operations.

The ideal candidate will play a pivotal role in enabling smart manufacturing, integrating ERP, MES, and IoT systems, and driving digital transformation aligned with Industry 4.0 principles.

Key Responsibilities

Strategic Leadership
Define and implement application development strategies that align with the company’s manufacturing and digital transformation goals.
Drive the adoption of Smart Manufacturing, Industry 4.0, and digital twin concepts through custom application ecosystems.
Collaborate with operations and engineering leadership to identify and execute application modernization programs.

Application Portfolio Oversight
Oversee core systems such as ERP, MES, SCM, PLM & WMS.
Ensure systems are fully integrated and provide real-time visibility into production, inventory, and logistics.

AI Integration with Manufacturing
Integrate AI models to analyze sensor data and forecast machine failures before they happen.
Enable AI-based forecasting in ERP/SCM systems to optimize inventory and reduce waste.
Implement computer vision to detect defects in production lines using real-time imagery.
Use AI to recommend optimal production schedules based on constraints like raw material availability, labor, and machine uptime.
Apply AI algorithms to optimize power consumption across plants and reduce operational costs.
Integrate AI services into existing platforms like MES, ERP, and PLM through APIs and microservices.

Team and Capability Building
Lead a cross-functional team of developers, solution architects, and product owners focused on manufacturing applications.
Promote continuous learning in emerging tech like edge computing, AI for predictive maintenance, and robotics integration.
Implement Agile and DevOps practices in a plant-floor-appropriate way (e.g., hybrid agile for regulated environments).

Operational Excellence and Support
Ensure uptime, availability, and performance of mission-critical applications across global manufacturing sites.
Implement robust change management processes to minimize disruption in high-availability production environments.
Lead root cause analysis for application-related production disruptions.

Stakeholder Engagement
Act as the bridge between IT and plant operations, procurement, engineering, and logistics.
Translate manufacturing KPIs into technical system requirements and solutions.
Influence strategic decisions around plant digitization and automation.

Data and Compliance Management
Ensure all applications are compliant with industry regulations.
Enforce cybersecurity standards, especially around OT (Operational Technology) and IT integration.
Champion data governance and real-time analytics to improve Overall Equipment Effectiveness.

Budget and Vendor Management
Manage budgets for application development, upgrades, and licensing.
Negotiate with software and system integrator vendors.
Evaluate build vs. buy decisions for application capabilities.

Logical Reasoning & Critical Thinking
The candidate must demonstrate strong logical reasoning skills to effectively analyze complex technical scenarios,
identify root causes, and make informed decisions that impact application architecture, operational efficiency, and system reliability in a manufacturing setting.

Travel
This role requires frequent travel to manufacturing units in China and India to engage with on-ground teams, understand operational processes, and align enterprise systems with real-world manufacturing workflows.

Required Skills & Experience

• 15+ years of experience in software development and architecture for large-scale, distributed platforms.
• At Least 5+ years of experience in leadership roles.
• Master’s degree in Computer Science, Information Technology, or a related field is required.
• Deep expertise in Java, J2EE, Python, SpringBoot, JavaScript, ReactJS, with strong system design and debugging skills.
• Deep knowledge of ERP/MES integration, smart factory solutions, and IoT platforms.
• Strong knowledge of Oracle, MySql and NoSQL databases, message queues, and distributed data systems.
• Hands-on experience with AI/ML model building, integration, including inference pipelines and model lifecycle management.
• Deep knowledge on SOLID Principles, Foundational Patterns, Enterprise Application Patterns and Cloud-Native and Microservices Patterns.
• Experience with AWS cloud components.
• Experience with cloud migrations and hybrid cloud/on-prem deployments.
• Familiarity with CI/CD, containerization (Docker), and orchestration tools (Kubernetes).
• Strong leadership in cross-site global environments.
• Familiar with manufacturing KPIs such as yield, downtime, throughput, lead time, and inventory turns.
• Security-first mindset: Knowledge of authentication, data protection, and compliance frameworks.
• Strong logical reasoning and critical thinking skills to analyze, optimize, and architect complex systems in dynamic enterprise environments.
• Excellent communication and collaboration skills in agile teams.

Preferred Qualifications

• Experience in Machine learning frameworks (e.g., Scikit-learn).
• Experience in deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience building recommendation systems, chatbots, or predictive services.
• Knowledge of backend observability, circuit breaking, and self-healing systems.
• Understanding of data governance, feature stores, and stream processing.
• AWS and AI certifications are a plus.