AI Solution Architect – Industrial AI | Confidential Employer | Riyadh, Saudi Arabia

Tech Junction Ltd; Riyadh; On-site; SAR 600,000 - 900,000; Full time

Job summary

Tech Junction Ltd in Riyadh invites an experienced AI Solution Architect to lead Industrial AI transformation initiatives in Oil & Gas and Refinery sectors. You will design and govern enterprise-grade AI solutions leveraging Generative AI, LLMs, RAG, cloud platforms, and advanced analytics to optimize operations.

The role requires 10+ years in AI/solution architecture, hands-on with Azure/AWS, MLOps, and AI governance.

Qualifications

• Bachelor’s or Master’s degree in CS, AI, DS, engineering, or related field.
• 10+ years of experience in Solution Architecture or enterprise technology leadership.
• Strong experience designing and implementing enterprise AI/ML solutions.
• Hands-on experience with Generative AI technologies.
• Strong knowledge of LLMs and RAG.
• Experience deploying AI solutions on Azure and AWS.
• Strong understanding of MLOps methodologies and AI operating frameworks.
• Experience with AI governance, model lifecycle management, and enterprise AI operations.
• Strong knowledge of Industrial Analytics and data-driven operational optimization.
• Excellent stakeholder management, communication, and solution leadership skills.

Responsibilities

• Design and architect enterprise-scale AI and Machine Learning solutions for industrial and refinery environments.
• Define AI platform architecture, governance models, and deployment standards.
• Lead solution design for Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) implementations.
• Design cloud-native AI solutions leveraging Microsoft Azure and Amazon Web Services (AWS).
• Establish MLOps frameworks to support model development, deployment, monitoring, and lifecycle management.
• Develop AI architecture roadmaps aligned with digital transformation and business objectives.
• Integrate industrial analytics solutions with enterprise platforms and operational systems.
• Collaborate with data engineering teams to build scalable AI-ready data platforms.
• Design intelligent solutions supporting predictive maintenance, operational optimization, yield improvement, anomaly detection, and industrial process intelligence.
• Establish AI governance, security, compliance, and responsible AI practices.
• Lead architectural reviews, technology evaluations, and solution design workshops.
• Provide technical leadership to AI engineers, data scientists, and development teams.
• Support stakeholder engagement, business case development, and AI adoption initiatives.
• Maintain architecture documentation, standards, frameworks, and best practices.

Skills

Generative AI

LLMs

RAG

Azure

AWS

MLOps

AI governance

Industrial analytics

Stakeholder management

Cloud architecture

Education

Bachelor's or Master's degree in CS/AI/DS/Engineering

Tools

Azure

AWS

Job description

Position Summary

An exciting opportunity is available for an experienced AI Solution Architect to lead Industrial AI transformation initiatives within the Oil & Gas and Refinery sectors. The successful candidate will be responsible for designing, architecting, and governing enterprise-grade Artificial Intelligence solutions that leverage Generative AI, Machine Learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), cloud platforms, and advanced analytics to optimize industrial operations and support digital transformation programs.

Detailed Job Description

As an AI Solution Architect, you will provide technical leadership for the design, implementation, and operationalization of scalable AI and Machine Learning solutions. You will work closely with business leaders, data engineers, AI engineers, refinery process experts, OT/IT teams, and enterprise stakeholders to transform industrial data into intelligent business capabilities.

The role requires deep expertise in enterprise AI architecture, cloud-native AI platforms, MLOps, AI governance, industrial analytics, and Generative AI technologies. You will be responsible for defining architecture standards, establishing AI operating models, leading AI solution delivery, and ensuring alignment with business and operational objectives.

This position offers the opportunity to work on large-scale industrial transformation programs that combine AI, data engineering, cloud computing, and advanced analytics to enhance operational efficiency, asset performance, predictive intelligence, and business decision-making.

Job Details

Location: Riyadh, Saudi Arabia
Industry: Industrial AI, Refinery, Oil & Gas
Experience Required: 10+ Years
Joining Requirement: Immediate

Key Responsibilities

• Design and architect enterprise-scale AI and Machine Learning solutions for industrial and refinery environments.
• Define AI platform architecture, governance models, and deployment standards.
• Lead solution design for Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) implementations.
• Design cloud-native AI solutions leveraging Microsoft Azure and Amazon Web Services (AWS).
• Establish MLOps frameworks to support model development, deployment, monitoring, and lifecycle management.
• Develop AI architecture roadmaps aligned with digital transformation and business objectives.
• Integrate industrial analytics solutions with enterprise platforms and operational systems.
• Collaborate with data engineering teams to build scalable AI-ready data platforms.
• Design intelligent solutions supporting predictive maintenance, operational optimization, yield improvement, anomaly detection, and industrial process intelligence.
• Establish AI governance, security, compliance, and responsible AI practices.
• Lead architectural reviews, technology evaluations, and solution design workshops.
• Provide technical leadership to AI engineers, data scientists, and development teams.
• Support stakeholder engagement, business case development, and AI adoption initiatives.
• Maintain architecture documentation, standards, frameworks, and best practices.

Required Qualifications & Skills

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.
• Minimum 10 years of experience in Solution Architecture, Artificial Intelligence, Data Science, or Enterprise Technology leadership.
• Strong experience designing and implementing enterprise AI/ML solutions.
• Expertise in AI/ML Solution Architecture and enterprise AI strategy.
• Hands-on experience with Generative AI technologies.
• Strong knowledge of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
• Experience deploying AI solutions on Microsoft Azure and AWS cloud platforms.
• Strong understanding of MLOps methodologies and AI operational frameworks.
• Experience with AI governance, model lifecycle management, and enterprise AI operations.
• Strong knowledge of Industrial Analytics and data-driven operational optimization.
• Excellent stakeholder management, communication, and solution leadership skills.
• Strong analytical thinking and business problem-solving capabilities.

Nice-to-Have Skills

• Oil & Gas industry experience.
• Refinery operations and process industry experience.
• Industrial AI deployment experience.
• Experience with digital transformation and Industry 4.0 initiatives.
• Knowledge of OT/IT convergence and industrial data ecosystems.
• AI platform implementation and modernization experience.
• Cloud architecture certifications.
• AI/ML, Data Science, or Enterprise Architecture certifications.
• Experience leading global or enterprise-scale transformation programs.

Why Apply?

• Lead transformative Industrial AI initiatives within the Oil & Gas and Refinery industries.
• Work with cutting-edge technologies including Generative AI, LLMs, RAG, MLOps, Azure, and AWS.
• Influence enterprise AI strategy, architecture, and innovation programs.
• Collaborate with multidisciplinary teams across AI, analytics, engineering, and operations.
• Drive digital transformation and intelligent industrial operations.
• Work on high-impact AI initiatives with measurable business value.
• Gain exposure to next-generation Industrial AI and enterprise technology ecosystems.