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Join Razor Labs, a leader in the mining tech sector, specializes in predictive maintenance with our flagship product, DataMind AI™. Our AI Sensor Fusion technology forecasts equipment failures, enhancing operational efficiency and safety.

Publicly traded on the Tel Aviv Stock Exchange, we have a strong presence in key mining regions, including Australia and South Africa, where our solutions have driven significant improvements.

As part of our team, you’ll collaborate with the brightest minds, tackling the most complex problems and shaping the future of industrial technology. Together, we can build smarter, greener and safer industries of tomorrow.

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Pre-Sales Engineer

Johannesburg, South Africa

About The Position

DataMind AI by Razor Labs fuses vibration, oil, pressure, temperature and vision data to predict failures early, cut unplanned downtime and extend asset life across fixed plant assets and mobile fleets. As a Pre-Sales Engineer, you are the technical bridge between business development and prospective customers clarifying needs, crafting solutions and showcasing how AI can transform mining operations.

Key Responsibilities:

  • Own the technical win from first discovery workshop through implementation hand-off.
  • Shape the solution: define use cases, success metrics and data readiness with reliability, OT and operations teams.
  • Prove value: design and deliver tailored demos, proof-of-value projects and RFP/RFI responses that highlight clear ROI.
  • Translate insights into executive-level value briefs and partner with Account Executives on proposals and negotiations.
  • Ensure a smooth hand-off: package all technical artifacts and stay the subject-matter expert until initial KPIs are achieved.
  • Close the feedback loop: capture South African-market needs (fixed assets, mobile equipment, ESG) and relay them to Product & Engineering.


Requirements


  • At least 5 years in a technical role supporting enterprise software/hardware in industrial settings (preferably mining or heavy industry).
  • Experience with predictive maintenance, reliability engineering, or condition monitoring systems – a plus.
  • Preferred: hands-on analysis of vibration, lubrication, thermography or similar data on fixed and mobile mining equipment plus sensor selection, installation and certification experience.
  • B.Eng. in Mechanical, Electrical, Instrumentation or Mining (or equivalent experience).
  • Familiarity with suites such as AVEVA Predictive Analytics, Aspen Mtell, OSIsoft PI, GE APM.
  • Category II or higher ISO 18436-2 vibration-analysis certification (or equivalent) – advantage.
  • Proven ownership of RFP/RFI responses and live demo environments that converted technical validation into signed deals.
  • Strong written and verbal communication skills, from shop floor to C-suite.
  • Mine-site safety compliant; ready for frequent short-notice travel.

Advantages:

  • Experience deploying disruptive technologies, PdM solutions or digital twins in heavy-industry environments.
  • Knowledge of reliability-centred maintenance and condition-based maintenance programmes.
  • Exposure to mobile-fleet health systems (Caterpillar MineStar, Modular Mining MineCare).
  • Basic ad-hoc analytics skills (Excel / Power BI / Python).


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