Senior Specialist - Artificial Intelligence & Machine Learning

Role Overview

Senior Specialist – Artificial Intelligence & Machine Learning at Al Ghurair Investment, joining the data and innovation team to lead the company's AI transformation journey.

Company Overview

Al Ghurair Investment (AGI) is undergoing AI transformation, seeking to design intelligent systems, automation workflows, and generative AI capabilities that enhance decision-making and operational efficiency across the enterprise.

Role Purpose

Design and deliver end-to-end AI/ML solutions using Large Language Models, Retrieval Augmented Generation, and agentic frameworks to solve business problems and drive measurable AI adoption across the organization.

Key Responsibilities

AI Solution Development & Delivery

• Design and deliver end-to-end AI/ML solutions from problem definition through production deployment using LLMs, RAG, and agentic frameworks to solve business problems.
• Develop, fine-tune, and evaluate models for use cases including document intelligence, process automation, forecasting, churn prediction, and business reporting.
• Build and optimize AI pipelines for data ingestion, retrieval, and contextual reasoning at enterprise scale.
• Develop Agentic AI systems and RAG pipelines for real-world enterprise applications.

Analysis & Modelling

• Apply exploratory data analysis, statistical techniques, and ML methods including time-series, regression, and tree-based models such as XGBoost to uncover insights and guide modelling decisions.
• Leverage prompt engineering, contextual reasoning, and knowledge retrieval techniques within Large Language Models.

MLOps & Production Excellence

• Maintain awareness of MLOps practices including model versioning, monitoring, drift detection, retraining, and CI/CD to ensure scalable, reliable production deployments.
• Ensure end-to-end AI solution delivery from experimentation and prototyping to production deployment and monitoring.

Governance & Ethics

• Maintain AI architectures, workflows, and documentation while championing ethical, transparent, and fair AI aligned with governance standards.

Collaboration & Innovation

• Collaborate with data engineers, developers, platform teams, and business stakeholders to translate requirements into deployable solutions and drive measurable impact.
• Continuously assess emerging AI trends and integrate best practices into the innovation roadmap.
• Communicate complex AI concepts to non-technical stakeholders.

Qualifications & Experience

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• 5–8 years of professional experience in Data Science, Machine Learning, or Applied AI roles.
• Proven expertise in Large Language Models and Generative AI, including prompt engineering, contextual reasoning, and knowledge retrieval.
• Hands-on experience developing Agentic AI systems and RAG pipelines for real-world enterprise applications.
• Experience in end-to-end AI solution delivery, from experimentation and prototyping to production deployment and monitoring.
• Strong understanding of data engineering principles, MLOps workflows, and vector-based search methodologies.

Skills & Competencies

• Strong programming skills in Python.
• Solid understanding of data preprocessing, model development, and deployment lifecycles.
• Proficiency in tree-based models such as XGBoost.
• Strong problem-solving mindset.
• Experience working in cross-functional, agile environments.
• Ability to drive measurable business outcomes through AI adoption.

Additional Information

• Professional certifications in AI/ML or cloud-based AI solutions are preferred.
• Additional credentials in Generative AI, Machine Learning Operations (MLOps), or Responsible AI are a plus.