As ProU Technology transitions toward automated safety solutions, this role serves as the critical link between traditional Process Safety Management (PSM) and advanced computational intelligence. You will be responsible for translating complex engineering physics and international standards into digital logic, ensuring that our AI-driven platforms produce technically sound and compliant safety deliverables.
Key Responsibilities
- Physics-Based Modeling: Implement and validate source-term, dispersion, fire, and explosion models within a Python-based framework to ensure accurate consequence assessments.
- AI Integration & Validation: Lead the engineering-side acceptance testing for AI-generated HAZOP reports, focusing on the accuracy of causes, consequences, and safeguard relevance.
- Computational Pipelines: Collaborate with ML Engineers to build and refine P&ID extraction pipelines, utilizing Computer Vision and OCR to identify process tags and ISA symbols accurately.
- Surrogate Development: Work on the development and training of Physics-Informed Neural Networks (PINNs) and Fourier Neural Operators (FNO) to create high-speed simulation surrogates for real-time risk assessment.
- Standard Compliance: Ensure all computational logic adheres to global standards such as API 2218, NFPA 30, and Saudi Aramco GI-0002.100.
- Software Orchestration: Assist the backend team in designing the orchestration layer for complex engineering simulations and data persistence.
Mandatory Technical Requirements
- Process Safety Expertise: Deep knowledge of HAZOP, QRA, and Consequence Modeling (Fire, Explosion, Dispersion).
- Python Proficiency: Strong coding skills in Python, specifically for data manipulation (Pandas, NumPy) and engineering calculations.
- Engineering Simulation: Hands-on experience with industry-standard software such as PHAST, SAFETI, Aspen HYSYS, or Flaresim.
- AI Literacy: Understanding of LLM prompting, OCR pipelines, and the application of machine learning in an industrial engineering context.
Qualifications & Experience
- Education: Bachelor's or Master's degree in Chemical or Mechanical Engineering.
- Experience: 5+ years in Process Safety and Risk Consulting, with a proven track record of using computational tools to solve complex safety problems.
- Standards: Familiarity with IP Model Code Pt. 19 and ISO 834 hydrocarbon fire curves.
