Process Simulation Twin & Optimization Engineer

Saudi Aramco; Dhahran Compound; On-site; SAR 600,000 - 900,000; Full time

Job summary

Saudi Aramco is seeking an experienced Process Simulation Twin (PST) and Optimization Engineer to deploy and sustain online process twins, linking real-time data with advanced models across the refinery portfolio. You will bridge thermodynamic rigor and hybrid analytics to deliver data-enabled improvements.

You will lead PST deployment, ensure data connectivity to historians and LIMS, monitor KPI performance, run what-if studies, and mentor operations and engineering teams.

Qualifications

• Bachelor’s degree in Chemical Engineering.
• 15+ years in Process Simulations, Online Modeling, or Real-Time Optimization.
• Experience with ROMeo; 20 years preferred.
• Strong understanding of refinery processes, mass and energy balances.
• Experience connecting simulations to live data sources (Data Historians, OPC).
• Data reconciliation and model tuning expertise.

Responsibilities

• Lead PST development, deployment, and sustainment with real-time data integration.
• Configure connectivity between plant historians, LIMS, and simulation software.
• Monitor facility health and identify performance gaps using PST.
• Maintain thermodynamic models representing process behavior.
• Perform offline studies and what-if scenarios.
• Act as liaison between data teams and Operations/Process Engineering.
• Lead optimization sessions for major process units (CDU/VDU, Hydrotreaters).
• Benchmark KPIs across facilities and develop best practices.
• Provide expert consulting and participate in technical exchanges.

Skills

Process simulation

Online modeling

Real-time optimization

Data reconciliation

Data integration

OPC connectivity

Thermodynamics

Model tuning

Education

Bachelor's degree in Chemical Engineering

Tools

ROMeo

OPC

Job description

Title: Process Simulation Twin & Optimization Engineer - Refinery Experience Only

Overview

We are seeking an experienced Process Simulation Twin (PST) and Optimization Engineer to join our Reliability Solutions Department (RSD) within our Global Manufacturing Excellence Center. Global Manufacturing Excellence (GME) is the recognized Center of Excellence driving value across Saudi Aramco’s Downstream Global manufacturing portfolio. Your primary role is to deploy and sustain online process simulations (process digital twins), perform process optimization activities to identify opportunities, monitor process performance KPIs and develop advanced process optimization data-enabled solutions. This role sits at the boundary of process engineering and digitalization beyond traditional process simulation roles. You will be responsible for bridging the gap between rigorous thermodynamic models, process digital twins, real-time process data and hybrid analytics through AI.

Key Responsibilities

As the successful candidate you will be required to perform the following:

• Lead the development, deployment, and sustainment of PST that integrate real-time process data with rigorous equation-oriented or sequential simulation engines in alignment with corporate objectives.
• Configure and troubleshoot the connectivity between plant historians, laboratory information systems, and simulation software to ensure seamless data ingestion and reconciliation.
• Utilize PST to perform automated monitoring of facility health, detecting deviations between ideal performance and actual plant operations to identify opportunity gaps.
• Develop and maintain thermodynamic models and mathematical equations that accurately represent the behavior of various processes ensuring the PST accurately reflects the current state of the facility (including heat exchanger fouling, catalyst decay, etc.).
• Perform offline engineering studies using PST to analyze complex operational problems, debottleneck constraints, and conduct "what-if" scenarios based on current operating conditions.
• Act as the technical liaison between data teams and Operations/Process Engineering teams, leading technical sessions on model architecture, data quality, and commissioning.
• Lead process optimization sessions to de-bottleneck key process units such as CDU/VDU, Hydrocrackers, Catalytic crackers, Diesel Hydrotreaters, Isomerization.
• Benchmark process optimization KPIs with 15+ operating facilities and provide development of programs, processes, guidelines and best practices.
• Provide subject matter expertise to operating facilities Operations, Maintenance, and Engineering teams by consulting, providing awareness sessions, and participating and leading technical exchanges and conferences.

Minimum Requirements

• Bachelor’s degree in Chemical Engineering.
• Minimum of 15 years of experience in Process Simulations, Online Modeling, or Real-Time Optimization (preferably ROMeo). 20 years of experience is preferred.
• Demonstrate expertise in process engineering and flowsheet-based processes simulation. Preferred Equation Oriented simulation.
• Comprehensive understanding of refinery facilities, feedstock/product movements, margins, giveaways, process yields, and mass and energy balances.
• Demonstrated experience connecting simulations to live data sources (Data Historians, OPC, etc.).
• Strong understanding of data reconciliation, model tuning, and dealing with gross errors in industrial data.

Work Location and Work Schedule

Work location: Within Saudi Arabia – To be specified in Job offer

Work schedule: Full Time - To be specified in Job offer

Job Posting Duration

Job posting start date: 02/16/2026

Job posting end date: 12/31/2026

Working environment

Our high-performing employees are drawn by the challenging and rewarding professional, technical and industrial opportunities we offer, and are remunerated accordingly. At Aramco, our people work on truly world-scale projects, supported by investment in capital and technology that is second to none.

We invest heavily in talent development and have a long history of educating and training our workforce through workforce development programs – one of the largest in the world.