LOCATION: SINGAPORE (ON-SITE)

Our client is a prestigious government-linked research institution focused on advancing integrated digital and manufacturing solutions. They are seeking a highly skilled Senior Software Engineer to lead the development of intelligent planning, scheduling, and manufacturing applications.

REQUIREMENTS

• Bachelor’s or Master’s degree in Computer Science, Engineering, Operations Research, or a related field.
• Minimum 5 years of software engineering experience with a focus on enterprise applications.
• Proficient in C# .NET and Angular development.
• Hands-on experience with Docker, Kubernetes, and cloud/on-premise deployment strategies.
• Solid understanding of optimization techniques and their application in planning/scheduling problems.
• Familiar with CI/CD workflows, version control, and secure coding practices.
• Experience in the manufacturing domain, particularly in inventory analytics and production planning.
• Exposure to SAP/ERP and advanced planning systems such as Siemens APS is a plus.Familiarity with generative AI use cases in industrial or planning systems is highly desirable.

ROLE

The Senior Software Engineer will be responsible for designing, developing, and deploying enterprise-level planning and scheduling platforms. This includes architecture of microservices, integrating AI/ML capabilities, and ensuring the scalability and robustness of the systems. The ideal candidate will bring strong experience in C#,.NET and Angular development, a deep understanding of manufacturing systems, and a passion for solving complex planning problems using optimization and AI techniques.

RESPONSIBILITIES

• Lead end-to-end development and maintenance of enterprise planning and scheduling systems.
• Architect scalable and maintainable microservices-based platforms.
• Integrate AI/ML components to enhance manufacturing intelligence and automation.
• Develop and manage containerized environments using Docker and Kubernetes.
• Collaborate with cross-functional teams to align solutions with business and operational requirements.
• Drive real-time data processing and visualization solutions for production monitoring.
• Implement DevSecOps best practices, including CI/CD pipelines for secure and efficient delivery.
• Evaluate and recommend emerging technologies to improve system performance and flexibility.
• Explore and incorporate generative AI capabilities to enhance system intelligence.