Engineer (Reliability)
Job highlights
- Rhovan Mine
- South Africa
- Brits, Northwest
Job ID
Rhovan - Engineer (Reliability)
Closing date
10/04/2026
Last Updated
01/04/2026
Glencore is one of the world's largest globally diversified natural resource companies and a major producer and marketer of more than 60 commodities. Our operations comprise of around 150 mining, metallurgical and oil production assets. Our purpose is to responsibly source the commodities that advance everyday life. Employing 135,000 people globally, people are at the heart of our business, and we aim to attract employees who strive to be leaders in their field.
In this role you will be responsible for:
• Coordinate, analyze, and report on all predictive maintenance alarms and status changes
• Provide daily reporting and escalation of critical (red) alerts
• Track asset health trends, including lead time to failure and degradation patterns
• Coordinate root cause analysis (RCA) using AI-driven insights
• Implement data-driven maintenance scheduling based on actual asset condition
• Compare predictive maintenance outcomes against maintenance spend, spares usage, and service costs
• Validate AI-recommended repairs and actions for accuracy and effectiveness
• Drive measurable reductions in unplanned downtime, emergency work, and premature component replacement
• Ensure data quality, transmission integrity, and system availability
• Integrate systems including Razor Labs, PLCs, SCADA, Komatsu fleet management, and fatigue management systems (TMM)
• Coordinate job card creation and maintenance execution through relevant work centres
• Manage sensor health, performance, and repairs
• Conduct regular audits of system performance, model accuracy, and unrealized opportunities
• Develop and track predictive maintenance and reliability KPIs
• Build internal capability in vibration analysis, condition monitoring, and reliability engineering through training and coaching
• Research and implement new technologies, models, and industry best practices
• Produce consolidated AI-driven reports linking operations, reliability, and plant performance
• Facilitate structured reviews of predictive maintenance programmes with service providers
• Provide clear, auditable reporting to support operational, financial, and capital decisions.
About you:
• BTech / BSc Eng in Mechanical, Electrical, Instrumentation Engineering, or Systems Engineering
• 8 years’ experience in engineering, AI/machine learning, predictive maintenance, or condition monitoring
• Knowledge of condition monitoring techniques and reliability metrics (MTBF, MTTR, availability, OEE)
• Experience with maintenance systems, project management, and plant operations
• Background in plant maintenance and maintenance systems
• Strong understanding of engineering principles
• Experience in heavy industry environments
• Valid driver’s license and own transport
• Strong interpersonal and people development skills
• Technical leadership, analytical thinking and problem-solving ability
• Effective cross-functional collaboration with engineering, operations, and external partners
• Proficient in English communication
• Medically fit
In this role you will be responsible for:
• Coordinate, analyze, and report on all predictive maintenance alarms and status changes
• Provide daily reporting and escalation of critical (red) alerts
• Track asset health trends, including lead time to failure and degradation patterns
• Coordinate root cause analysis (RCA) using AI-driven insights
• Implement data-driven maintenance scheduling based on actual asset condition
• Compare predictive maintenance outcomes against maintenance spend, spares usage, and service costs
• Validate AI-recommended repairs and actions for accuracy and effectiveness
• Drive measurable reductions in unplanned downtime, emergency work, and premature component replacement
• Ensure data quality, transmission integrity, and system availability
• Integrate systems including Razor Labs, PLCs, SCADA, Komatsu fleet management, and fatigue management systems (TMM)
• Coordinate job card creation and maintenance execution through relevant work centres
• Manage sensor health, performance, and repairs
• Conduct regular audits of system performance, model accuracy, and unrealized opportunities
• Develop and track predictive maintenance and reliability KPIs
• Build internal capability in vibration analysis, condition monitoring, and reliability engineering through training and coaching
• Research and implement new technologies, models, and industry best practices
• Produce consolidated AI-driven reports linking operations, reliability, and plant performance
• Facilitate structured reviews of predictive maintenance programmes with service providers
• Provide clear, auditable reporting to support operational, financial, and capital decisions.
About you:
• BTech / BSc Eng in Mechanical, Electrical, Instrumentation Engineering, or Systems Engineering
• 8 years’ experience in engineering, AI/machine learning, predictive maintenance, or condition monitoring
• Knowledge of condition monitoring techniques and reliability metrics (MTBF, MTTR, availability, OEE)
• Experience with maintenance systems, project management, and plant operations
• Background in plant maintenance and maintenance systems
• Strong understanding of engineering principles
• Experience in heavy industry environments
• Valid driver’s license and own transport
• Strong interpersonal and people development skills
• Technical leadership, analytical thinking and problem-solving ability
• Effective cross-functional collaboration with engineering, operations, and external partners
• Proficient in English communication
• Medically fit