Graduate Maintenance Systems & AI Development Engineer

Salary: Market Related

Location: Germiston

Employment type: 12 month fixed-term contract

Working arrangement: On-site

Our client is seeking a Graduate Maintenance Systems & AI Development Engineer to help design, build and implement a maintenance and asset management platform. Working with senior engineering leadership and software developers, the successful candidate will support asset management, equipment reliability and the development of AI-supported maintenance solutions.

Responsibilities

• Develop equipment asset registers, asset hierarchies and equipment coding standards.


• Collect and verify equipment technical data, assess equipment criticality and assist with maintenance Bills of Materials.


• Establish maintenance task libraries and preventive maintenance strategies.


• Gather user requirements, document maintenance workflows and translate engineering needs into software development specifications.


• Assist with the design, configuration, testing and deployment of maintenance and asset management systems.


• Develop dashboards, reports and tools to monitor maintenance performance indicators.


• Identify opportunities for AI-supported workflows, predictive maintenance and mobile inspection solutions.


• Build datasets for future machine learning applications and evaluate technologies for maintenance optimisation.


• Analyse equipment performance and failure data, support root cause investigations and assist with maintenance strategy optimisation.


• Capture, clean and maintain accurate maintenance data, and develop standard operating procedures and work instructions.

Requirements

• Grade 12/Matric.


• BEng or BSc Eng in Mechanical, Industrial, Mechatronic or Electrical Engineering, or a related field.


• 0–5 years’ working experience. Graduate applications are encouraged.


• Exposure to maintenance environments would be advantageous.


• Knowledge of computerised maintenance management systems (CMMS), enterprise asset management systems (EAMS), reliability engineering principles and asset management concepts.


• Knowledge of data analytics and AI tools and applications.


• Knowledge of Microsoft Power Platform, Excel, Power BI and C#.NET.


• Exposure to Python, SQL, SYSPRO, database design, AI-assisted software development or machine learning fundamentals would be advantageous.