AI Engineer (PMC) – Project Management Workflow Optimisation

KBR Inc.; United Arab Emirates; On-site; AED 120,000 - 200,000; Full time

Job summary

A global engineering firm is seeking an AI Engineer to design and implement AI-driven solutions focused on optimizing project management workflows. This role demands strong programming skills, knowledge of AI frameworks, and the ability to collaborate with engineers and project teams. The ideal candidate will possess experience in the Oil & Gas sector and a passion for leveraging AI technologies to enhance operational efficiency. This position offers an exciting opportunity to integrate artificial intelligence into project optimization initiatives.

Qualifications

• Strong programming skills in Python, R, or similar languages.
• Experience with AI/ML frameworks and LLMs.
• Understanding of project management principles and EPC workflows.
• Familiarity with Oil & Gas industry standards.

Responsibilities

• Design, develop, and implement AI-driven solutions.
• Analyze existing project management processes.
• Develop AI-powered tools for scheduling and risk prediction.
• Integrate AI systems with existing platforms.

Skills

Python

R

TensorFlow

PyTorch

MLOps tools

Excellent problem-solving skills

Strong communication

Tools

MLflow

Docker

AWS

Azure

MS Project

Primavera

SAP PM

Job description

AI Engineer (PMC) – Project Management Workflow Optimisation

Job Purpose

The AI Engineer will design, develop, and implement AI-driven solutions to optimise project management workflows, enhance operational efficiency, and support strategic decision-making. This role involves leveraging machine learning, automation, and predictive analytics to streamline processes across planning, execution, and monitoring phases of projects.

Key Responsibilities

• Workflow Automation & Optimisation
  • Analyse existing project management processes to identify inefficiencies and automation opportunities.
  • Develop AI-powered tools for scheduling, resource allocation, and risk prediction.
• AI Model Development
  • Design, train, and deploy machine learning models for predictive analytics (e.g., cost forecasting, delay risk assessment).
  • Implement Generative AI solutions for document summarisation, reporting, and stakeholder communication.
  • Implement Generative AI solutions for document review.
• Integration & Implementation
  • Integrate AI systems with existing platforms ensuring seamless data flow.
  • Develop APIs and automation scripts for interoperability across project management tools.
• Data Management & Analysis
  • Collect, clean, and analyse large datasets from project operations.
  • Build dashboards for real-time insights into project health, KPIs, and resource utilisation.
• Collaboration & Training
  • Work closely with project engineers, planners, and IT teams to align AI solutions with business needs.
  • Conduct workshops and training sessions on AI tools for project teams.

Required Skills & Qualifications

• Technical Expertise
  • Strong programming skills (Python, R, or similar).
  • Experience with AI/ML frameworks (TensorFlow, PyTorch) and LLMs (GPT, LangChain).
  • Knowledge of MLOps tools (MLflow, Docker) for model lifecycle management.
• Domain Knowledge
  • Understanding of project management principles and EPC workflows.
  • Familiarity with Oil & Gas industry standards and compliance requirements.
• Soft Skills
  • Excellent problem-solving and analytical skills.
  • Strong communication and stakeholder management abilities.

Experience Requirements

• Minimum 3–5 years in AI engineering or data science roles, preferably in industrial or project environments.
• Proven track record of deploying AI solutions that improved operational efficiency.

Desirable Competencies

• Strong understanding of project management methodologies (e.g., Agile, PMI, EPC workflows).
• Experience in AI-driven project scheduling and resource optimisation.
• Ability to design risk prediction models for cost overruns and delays.
• Familiarity with workflow automation tools and integration with project management platforms (MS Project, Primavera, SAP PM).
• Knowledge of data-driven decision-making and KPI dashboards for project performance monitoring
• Experience with cloud platforms (AWS, Azure) for scalable AI deployment.