Technical Engineer (Learning Applications)

Mindteck Singapore Pte Ltd; Hong Kong; On-site; HKD 368,000 - 552,000; Full time

Job summary

Mindteck Singapore Pte Ltd seeks a Technical Engineer with AI capabilities to support development and deployment of learning applications, including LMS platforms and related tools.

The role emphasizes designing intelligent features, improving user experience, and content discovery, while collaborating with data engineers and instructional designers to implement AI-driven personalization and secure deployment.

Qualifications

• Experience developing and deploying learning applications (LMS) or learning technology platforms.
• Ability to design, integrate, and maintain AI-powered features in learning platforms.
• Familiarity with SCORM/xAPI/LTI and e-learning standards is a plus.

Responsibilities

• Develop, customize, and maintain learning applications such as LMS and digital platforms.
• Design and integrate AI-powered features like recommendation engines and chatbots.
• Integrate LMS with enterprise systems via APIs and middleware.
• Conduct testing and performance optimization for both application and AI components.
• Collaborate with instructional designers, project managers, and product teams to translate requirements into technical solutions.
• Maintain technical documentation for system architecture, integrations, and AI components.

Skills

Python

JavaScript

C#

Java

HTML5

CSS

REST APIs

microservices

LMS

Relational Databases

Education

Bachelor’s degree in Computer Science/IT/Engineering

Tools

TensorFlow

PyTorch

Scikit-learn

Job description

Singaporean Only

Technical Engineer – (AI & Learning Applications)

Job Overview:

We are looking for a Technical Engineer with AI competencies to support the development and implementation of digital learning applications, including Learning Management Systems (LMS) and other learning technology platforms.

This role involves designing, integrating, and maintaining intelligent learning solutions that enhance user experience, personalize learning pathways, and improve platform capabilities through AI technologies. The ideal candidate will combine strong software engineering skills with knowledge of AI tools and technologies applied to learning environments.

Key Responsibilities:

Learning Application Development

• Develop, customize, and maintain learning applications such as Learning Management Systems (LMS) and other digital learning platforms.
• Support system implementation, configuration, and deployment of learning technologies.
• Ensure applications are scalable, secure, and aligned with system architecture standards.

AI Integration & Development

• Design and integrate AI-powered features into learning platforms, such as recommendation engines, chatbots, or adaptive learning tools.
• Work with AI frameworks and APIs to enhance learning analytics, learner engagement, and personalization.
• Explore and implement AI-driven solutions to improve content discovery, learner support, and performance tracking.

System Integration

• Integrate LMS platforms with other enterprise systems (e.g., HR systems, authentication systems, analytics platforms) using APIs and middleware.
• Ensure compatibility with e-learning standards such as SCORM, xAPI, or LTI.

Testing & Optimization

• Conduct system testing, debugging, and performance optimization for both application and AI components.
• Monitor platform performance and identify opportunities for improvement.

Collaboration

• Work closely with instructional designers, project managers, and product teams to translate learning requirements into technical solutions.
• Collaborate with data engineers and AI specialists to implement machine learning models and intelligent features.

Documentation & Support

• Maintain technical documentation for system architecture, integrations, and AI components.
• Provide technical troubleshooting and support during system implementation and deployment.

Skills & Experience Required:

• Technical Skills: Experience in software development using languages such as Python, JavaScript, C# or Java, Knowledge of web technologies such as HTML5, CSS, REST APIs, and microservices architecture and experience working with Learning Management Systems (LMS) or learning technology platforms. Hands‑on experience in implementing databases using platforms such as Microsoft SQL Server, MySQL, PostgreSQL or similar relational database systems
• AI & Data Competencies: Familiarity with AI or machine learning frameworks such as TensorFlow, PyTorch, or Scikit‑learn, Experience integrating AI APIs or services (e.g., NLP, recommendation engines, chatbot frameworks) and understanding of learning analytics, data processing, or AI-driven personalization.
• Systems & Integration: Experience integrating enterprise systems through APIs or middleware, understanding of cloud platforms such as AWS, Azure, or Google Cloud, Familiarity with SCORM, xAPI, LTI, or digital learning standards is an advantage.
• Soft Skills: Strong problem-solving and analytical thinking skills, ability to work in cross-functional project teams and good communication skills to translate technical concepts into practical solutions.
• Systems Administration: Knowledge of system administration, including managing user access, data backups, and security protocols in cloud-based environments.
• Project Collaboration: Experience working in a collaborative, cross-functional environment, interacting with technical and non-technical stakeholders.
• Attention to Detail: Ability to work with precision, ensuring all configurations, customizations, and integrations meet required specifications and standards.
• Communication Skills: Strong verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Education: Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
• Certifications: Relevant certifications in AI, cloud platforms, or software engineering are an advantage. (e.g., Machine Learning, AWS, Microsoft, LMS-specific certifications).
• Experience with Cloud-Based Systems: Experience with cloud platforms like AWS, Azure, or Google Cloud, particularly in the context of learning platforms
• Experience with SCORM/xAPI: Familiarity with e-learning standards like SCORM, xAPI, and Tin Can API for tracking and reporting learning activities.
• Familiarity with Data Security: Knowledge of data security practices, especially as they apply to sensitive learning and employee data.