Technical Engineer (AI & Learning Applications)

Mindteck Singapore Pte Ltd; Hong Kong; On-site; HKD 432,000 - 740,000; Full time

Job summary

Mindteck Singapore Pte Ltd is seeking a Technical Engineer with AI competencies to support the development and deployment of digital learning applications, including LMS platforms and related technologies. The role combines software engineering with AI to personalize learning experiences and enhance platform capabilities.

The candidate will design, develop, and integrate AI-powered features, ensure scalable and secure solutions, and collaborate with data engineers and instructional designers to

Qualifications

• Proficient in software development with Python/JavaScript/C#/Java.
• Experience with LMS or learning technology platforms is required.
• Knowledge of AI tools and technologies applied to learning environments.

Responsibilities

• Develop, customize, and maintain learning applications (LMS and related platforms).
• Design AI-powered features (recommendations, chatbots, adaptive learning).
• Integrate LMS with enterprise systems via APIs; ensure SCORM/xAPI/LTI compatibility.
• Conduct testing, debugging and performance optimization for AI components and apps.
• Collaborate with instructional designers, project managers, and product teams.
• Maintain technical documentation for system architectures, integrations, and AI components.

Skills

Python

JavaScript

C#

Java

REST APIs

microservices

LMS

AI frameworks

Learning platforms

Education

Bachelor's degree in Computer Science / IT / Engineering

Tools

TensorFlow

PyTorch

Scikit-learn

AWS

Azure

Google Cloud

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.