Job description
Job Scope:
- Lead end-to-end delivery of large-scale AI programs for upstream and refinery customers – from initiation to deployment and handover
- Define program scope, milestones, budget, and success criteria in collaboration with customers and internal stakeholders
- Manage cross-functional teams including software engineers, AI/ML engineers, QA, UI/UX, and domain experts
- Develop and maintain program schedules, resource allocation plans, cost tracking, and risk registers
- Facilitate agile ceremonies – sprint planning, daily standups, retrospectives, and release planning for AI product delivery
- Engage directly with oil & gas customers to gather requirements, manage expectations, and ensure alignment on predictive maintenance outcomes
- Translate customer operational needs (asset health monitoring, work order automation, RCA, integrity management) into executable program plans
- Coordinate with surface asset experts to validate AI model outputs against real-world failure modes and maintenance strategies
- Manage program budgets, track actuals vs. planned, and report financial health to leadership
- Identify, assess, and mitigate program risks – including data availability, model performance, integration challenges, and customer adoption
- Drive continuous improvement in delivery processes, engineering best practices, and customer satisfaction
- Document program decisions, lessons learned, and best practices for organizational knowledge
- Support sales and pre-sales teams with program estimates, resource planning, and customer presentations
Requirements:
- 10+ years of experience in program/project management, with at least 5+ years in Oil & Gas upstream or refinery domains
- Bachelor's or Master's degree in Engineering (Mechanical, Chemical, Petroleum, Computer Science) or Business Administration (or an equivalent qualification)
- Proven track record of delivering large-scale programs involving predictive maintenance, reliability, or asset integrity solutions
- Strong understanding of surface assets (compressors, turbines, heat exchangers, separators, pipelines, wellheads, pumps, valves, pressure vessels)
- Experience working with predictive maintenance solutions – condition monitoring, vibration analysis, oil analysis, RUL prediction, anomaly detection
- Solid understanding of AI/ML technologies and their application in industrial settings (predictive models, LLMs, agentic AI, RAG)
- Strong project management skills – agile/scrum, resource planning, costing/budgeting, risk management, and stakeholder communication
- Experience working in similar industrial AI product companies or consulting organizations
- Excellent leadership and team management skills – ability to lead cross-functional teams including engineers, data scientists, and domain experts
- PMP, PgMP, CSM, or SAFe certification is highly preferred
Job summary
This role demands a leader who has worked in similar industrial AI setups and understands the unique challenges of deploying AI solutions in asset
Pay: RM12,000.00 - RM15,000.00 per month
Benefits:
- Opportunities for promotion
- Professional development
Work Location: Remote