Engineer, AI

ST ENGINEERING LAND MRO & SERVICES PTE. LTD.; Singapore; On-site; SGD 50,000 - 90,000; Full time

Job summary

ST ENGINEERING LAND MRO & SERVICES PTE. LTD. in Singapore seeks a motivated individual to collaborate with engineering, operations and quality teams to design digital tools that streamline maintenance workflows.

The role emphasizes gathering requirements, data validation for pilot projects, and supporting end-to-end change management, including documentation and training. You will gain hands-on experience with AI-assisted tools and automation frameworks to drive data-driven decisions.

Qualifications

• Familiarity with software development principles and at least one programming language.
• Proactive learner who can work independently in a fast-paced environment.
• Strong communication and teamwork skills.
• Experience with full-stack development (frontend and backend).
• Interest in automation, data analytics, AI-enabled systems, or low-code/no-code platforms.
• Ability to map and analyze workflows to identify automation opportunities.
• Knowledge of enterprise data platforms, APIs, and systems integration.
• Experience in Data Science and ML model development; AI/ML/cloud certifications are a plus.

Responsibilities

• Gather requirements with multidisciplinary teams and translate into viable digital tools.
• Collect and analyze data for pilot projects to support performance monitoring.
• Assist with end-to-end change management, including user engagement, documentation, and training materials.
• Ensure governance, cybersecurity, and operational standards are followed for digital solutions.
• Contribute to continuous improvement programs focusing on digitalisation and automation.
• Work on AI-assisted tools and automation frameworks to build data-driven applications.

Skills

Programming basics

Self-motivated learner

Communication skills

Full-stack development

Automation & AI interest

Process mapping

APIs & integrations

Data analytics fundamentals

Tools

APIs

Low-code/no-code

Data platforms

Job description

Job Description:

• Collaborate closely with multidisciplinary teams—including engineering, operations, and quality assurance—to gather requirements and translate them into viable and user-friendly digital tools.
• Assist in gathering, validating, and analysing data critical for pilot projects, ensuring accuracy and relevance to support performance monitoring and continuous improvement efforts.
• Support end-to-end change management activities, including engaging users, creating comprehensive documentation, and training materials, and providing assistance during the rollout phases to ensure smooth adoption.
• Ensure all digital solutions comply with organisational governance, cyber security policies, and operational standards to maintain integrity and reliability.
• Support and actively contribute to continuous improvement programmes, focusing on digitalisation and automation initiatives aimed at streamlining workflows and enhancing operational efficiency.
• Develop hands-on expertise by working on AI-assisted tools and automation frameworks, assisting in building predictive, data-driven applications that support informed decision-making.

Job Requirements

• Basic understanding of software development principles with practical experience or coursework in at least one programming language or development platform.
• A proactive, self-motivated learner with the capacity to work independently and adapt to evolving priorities within a fast-paced and dynamic environment.
• Strong communication skills paired with a collaborative mindset, enabling effective teamwork and stakeholder engagement.
• Familiarity or experience in full-stack development covering both frontend and backend technologies.
• An interest in or previous exposure to automation technologies, data analytics methodologies, AI-enabled systems, or low-code/no-code development platforms.
• Ability to map and analyses operational processes and workflows, identifying opportunities for automation and system enhancements to eliminate inefficiencies.
• Knowledge of enterprise data platforms, APIs, and systems integration.
• Experience in Data Science and Machine Learning model development. Industry certifications in AI/ML, cloud, or enterprise architecture.