Ma'aden

Director, Industrial Artificial Intelligence

Riyadh, Saudi ArabiaPosted 2 weeks ago

Apply link checked yesterday

Salary
AED 12k–24k a month· est.
Job type
Full time
Level
Lead
Field
AI & Machine Learning
Work mode
On site

About the role

Maaden, established in 1997, is one of the fastest-growing mining companies in the world and the largest multi-commodity mining and metals company in the Middle East. We are leading the development of the mining industry to become the third pillar of Saudi Arabia’s economy by building a world-class, unique, and fully integrated mining value chain. We are pleased to share an exciting opportunity for the below mentioned position. This role offers a chance to contribute to our ambitious growth and play a key part in shaping the future of mining in the Kingdom. Job Title: Director, Industrial Artificial Intelligence Reporting To: Vice President, Artificial Intelligence Business Unit / Function: Technology & Innovation - Artificial Intelligence Department: Industrial Artificial Intelligence Why This Role Matters Industrial Artificial Intelligence enables Maaden to turn operational data and emerging AI capabilities into safer, more productive, reliable, and efficient operations across exploration, mining, mineral processing, and industrial assets. The Director, Industrial Artificial Intelligence shapes the strategy and portfolio that convert high-value operational challenges into scalable AI solutions. The role connects deep operational priorities with AI, data, digital, OT, and engineering capabilities to improve safety, productivity, recovery, reliability, process stability, energy efficiency, and sustainability. The role creates lasting value by moving Industrial AI beyond experimentation into production and sustained operational adoption, while building the capabilities, governance, partnerships, and responsible AI practices required to scale impact across Ma’aden. What You Will Deliver Industrial AI Strategy & Portfolio - Shape and evolve Maaden’s Industrial AI strategy and investment portfolio, directing resources toward opportunities with the strongest strategic, operational, and economic value. - Translate exploration, mining, processing, and asset performance priorities into a balanced portfolio of scalable AI opportunities with clear value, feasibility, risk, and adoption criteria. - Establish the operating model, standards, and governance required to scale Industrial AI responsibly and consistently across operations. Operational Performance & Value - Drive measurable improvements across safety, productivity, recovery, reliability, process stability, cost, energy efficiency, and sustainability through targeted Industrial AI solutions. - Advance AI-enabled decision-making across exploration, geology, mine planning and operations, mineral processing, process control, maintenance, and asset performance. - Move high-value AI initiatives from experimentation through production and adoption to sustained operational ownership and measurable benefits realization. Scalable AI & Technology Integration - Lead the development and deployment of production-grade AI capabilities that address complex industrial and operational challenges at scale. - Enable effective integration of AI with operational technology, control systems, historians, fleet systems, digital twins, laboratory platforms, and relevant enterprise technology. - Leverage enterprise AI platforms, reusable capabilities, architecture standards, and lifecycle controls to accelerate deployment while reducing duplication and technology risk. Governance & Operational Assurance - Govern Industrial AI solutions across model performance, reliability, cybersecurity, data governance, explainability, operational safety, and responsible AI requirements. - Establish transparent portfolio performance, value tracking, and risk oversight to enable informed investment and scaling decisions. - Ensure Industrial AI initiatives meet approved quality, financial, technical, risk, and performance expectations throughout their lifecycle. People, Partnerships & Enterprise Adoption - Build and lead an integrated Industrial AI function spanning exploration, mining, mineral processing, and industrial operations, strengthening both AI capability and operational domain expertise. - Build senior partnerships across operations, engineering, Digital, OT, IT, Enterprise AI, and business functions to embed AI into operational decisions and workflows. - Develop strategic relationships with technology providers, OEMs, universities, research institutions, and specialist organizations to accelerate innovation, capability development, and access to emerging technologies. What Success Looks Like - A prioritized Industrial AI portfolio delivers demonstrable operational and financial value aligned with Ma’aden’s strategic priorities. - AI solutions contribute measurable improvements in safety, productivity, recovery, reliability, process stability, energy efficiency, cost, and sustainability. - High-value AI use cases progress successfully from experimentation into production, sustained adoption, and operational ownership. - Industrial AI solutions demonstrate reliable performance with effectiv

Responsibilities

  • Industrial AI Strategy & Portfolio
  • - Shape and evolve Maaden’s Industrial AI strategy and investment portfolio, directing resources toward opportunities with the strongest strategic, operational, and economic value.
  • - Translate exploration, mining, processing, and asset performance priorities into a balanced portfolio of scalable AI opportunities with clear value, feasibility, risk, and adoption criteria.
  • - Establish the operating model, standards, and governance required to scale Industrial AI responsibly and consistently across operations.
  • Operational Performance & Value
  • - Drive measurable improvements across safety, productivity, recovery, reliability, process stability, cost, energy efficiency, and sustainability through targeted Industrial AI solutions.
  • - Advance AI-enabled decision-making across exploration, geology, mine planning and operations, mineral processing, process control, maintenance, and asset performance.
  • - Move high-value AI initiatives from experimentation through production and adoption to sustained operational ownership and measurable benefits realization.
  • Scalable AI & Technology Integration
  • - Lead the development and deployment of production-grade AI capabilities that address complex industrial and operational challenges at scale.
  • - Enable effective integration of AI with operational technology, control systems, historians, fleet systems, digital twins, laboratory platforms, and relevant enterprise technology.
  • - Leverage enterprise AI platforms, reusable capabilities, architecture standards, and lifecycle controls to accelerate deployment while reducing duplication and technology risk.
  • Governance & Operational Assurance
  • - Govern Industrial AI solutions across model performance, reliability, cybersecurity, data governance, explainability, operational safety, and responsible AI requirements.
  • - Establish transparent portfolio performance, value tracking, and risk oversight to enable informed investment and scaling decisions.
  • - Ensure Industrial AI initiatives meet approved quality, financial, technical, risk, and performance expectations throughout their lifecycle.
  • People, Partnerships & Enterprise Adoption
  • - Build and lead an integrated Industrial AI function spanning exploration, mining, mineral processing, and industrial operations, strengthening both AI capability and operational domain expertise.
  • - Build senior partnerships across operations, engineering, Digital, OT, IT, Enterprise AI, and business functions to embed AI into operational decisions and workflows.
  • - Develop strategic relationships with technology providers, OEMs, universities, research institutions, and specialist organizations to accelerate innovation, capability development, and access to emerging technologies.

Skills

  • Industrial AI
  • AI strategy
  • portfolio management
  • operational technology integration
  • data governance
  • cybersecurity
  • explainability
  • risk management
  • stakeholder management
  • digital transformation
  • mining & minerals processing
  • asset performance
  • production-grade AI deployment
  • governance and compliance

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