Engineer, AI

St Engineering; Singapore; On-site; SGD 56,000 - 89,000; Full time

Job summary

ST Engineering is seeking a motivated participant to work on digital tool initiatives across engineering, operations, and quality assurance. You will help translate requirements into practical tools, analyze data for pilot projects, and support change management with thorough documentation and training materials.

You will engage in automation and AI-enabled systems, learning to map processes, integrate APIs, and contribute to governance and security standards while improving operational

Qualifications

• Basic understanding of software development principles.
• Proactive, self-motivated learner with ability to work independently.
• Strong communication and collaboration skills.
• Familiarity 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 improve operational processes for automation.
• Knowledge of APIs and systems integration.
• Experience in Data Science and ML model development. Certifications in AI/ML/cloud/enterprise architecture are a plus.

Responsibilities

• Collaborate with multidisciplinary teams to gather requirements and translate them into viable digital tools.
• Assist in gathering, validating, and analysing data for pilot projects to support monitoring and improvement.
• Support end-to-end change management with user engagement, documentation, and training materials.
• Ensure digital solutions comply with governance, cyber security policies, and operational standards.
• Contribute to continuous improvement initiatives focusing on digitalisation and automation to streamline workflows.
• Develop hands-on expertise with AI-assisted tools and automation frameworks.

Skills

Software development

Independent learner

Communication skills

Full-stack development

Automation technologies

Data analytics

AI exposure

Tools

APIs

Low-code/no-code

Enterprise data platforms

Data science

ML model development

Job description

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• 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.