AI Engineer

Urban Ridge Supplies; Dubai; On-site; AED 300,000 - 480,000; Full time

Job summary

GEI is seeking an AI Engineer to develop and deploy AI-driven solutions that integrate pretrained models, Copilot technologies and enterprise data sources. The role emphasizes security, scalability and maintainability across production environments.

You will work closely with solution architects and platform teams to ensure AI solutions are production-ready and capable of scaling across use cases, building telemetry and monitoring into deployments.

Qualifications

• 4+ years of software engineering experience with at least 1 year building Generative AI applications.
• Experience with Generative AI LLMs including domain-specific fine-tuning.
• Proficiency in Python, PySpark, R or SQL.
• Experience delivering Generative AI solutions on Azure.
• Familiarity with Azure AI library APIs and Databricks Mosaic.

Responsibilities

• Build and deploy AI-based solutions using pretrained models and Copilot technologies.
• Design prompt flows, plugins, and orchestrations using Copilot Studio and Azure Functions.
• Integrate AI capabilities into business workflows and applications.
• Securely integrate enterprise data sources including APIs, Graph connectors and RAG.
• Maintain and optimize dashboards that support AI-enabled workflows.
• Instrument AI solutions for telemetry, reliability and cost control.
• Provide technical support for deployed AI solutions.
• Identify risks and support mitigation with architecture and platform teams.

Skills

Python/PySpark/R/SQL

Generative AI/LLMs

Azure cloud services

Security & compliance

Telemetry & monitoring

Tools

Azure AI APIs

Databricks

TensorFlow

PyTorch

GPT/Codex/DALL·E

Job description

Your role at GEI

The AI Engineer is responsible for the development of AI solutions typically leveraging pretrained models and copilots to support GEI s priority digital and AI initiatives This role focuses on building deploying and integrating AI capabilities into business workflows in a secure scalable and maintainable manner The AI Engineer plays a hands‑on role in active AI Solutions Factory use cases by implementing AI‑based solutions integrating enterprise data sources and supporting solution reliability and performance This role works closely with solution architects and platform teams to ensure AI solutions are production‑ready aligned with GEI standards and capable of scaling across use cases

Essential Responsibilities

• amp Duties Build and deploy AI‑based solutions using pretrained models and Copilot technologies
• Design and implement prompt flows plugins and orchestrations using Copilot Studio and Azure Functions
• Integrate AI capabilities into business workflows and applications
• Integrate enterprise data sources securely including APIs Graph connectors retrieval‑augmented generation RAG and event‑driven patterns
• Maintain and optimize Power BI dashboards that support AI‑enabled workflows and insights
• Instrument AI solutions for telemetry reliability performance monitoring and cost control
• Provide technical support and troubleshooting for deployed AI solutions
• Identify implementation risks and support mitigation strategies in collaboration with architecture and platform teams

Minimum Qualifications

• 4 years of software engineering experience with at least 1 year building Generative AI applications
• Experience with Generative AI Large Language Models LLMs including solution development and fine‑tuning for domain‑specific tasks
• Proficiency in at least one programming language such as Python PySpark R or SQL
• Experience delivering Generative AI LLM solutions preferably on Azure
• Familiarity with Azure AI library APIs including GPT Codex and DALL E and other frameworks e g Databricks Mosaic for integrating Generative AI into business workflows
• Knowledge of big data technologies such as Spark and Databricks familiarity with TensorFlow and PyTorch is a plus
• Knowledge of Azure cloud services including Azure AI Platform Azure Data Factory Azure Synapse and Azure Cognitive Services and their integration with ML workflows
• Familiarity with AI ethics bias mitigation explainability techniques and responsible AI practices
• Knowledge of security best practices for AI solutions including data encryption access control and endpoint protection
• Prior experience implementing AI ML solutions in professional services engineering or construction environments is a plus
• Azure or Databricks certifications e g Azure AI Engineer Associate Azure Solutions Architect Expert Databricks ML Professional Databricks Data Engineer Professional are a plus

Physical Requirements WORK ENVIRONMENT Functional Demands

• 4+ years of software engineering experience, with at least 1 year building Generative AI applications.
• Experience with Generative AI Large Language Models (LLMs), including solution development and fine‑tuning for domain‑specific tasks.
• Proficiency in at least one programming language such as Python, PySpark, R, or SQL.
• Experience delivering Generative AI (LLM) solutions, preferably on Azure.
• Familiarity with Azure AI library APIs, including GPT, Codex, and DALL E, and other frameworks (e.g., Databricks Mosaic) for integrating Generative AI into business workflows.
• Knowledge of big data technologies such as Spark and Databricks; familiarity with TensorFlow and PyTorch is a plus.
• Knowledge of Azure cloud services, including Azure AI Platform, Azure Data Factory, Azure Synapse, and Azure Cognitive Services, and their integration with ML workflows.
• Familiarity with AI ethics, bias mitigation, explainability techniques, and responsible AI practices.
• Knowledge of security best practices for AI solutions, including data encryption, access control, and endpoint protection.
• Prior experience implementing AI/ML solutions in professional services, engineering, or construction environments is a plus.
• Azure or Databricks certifications (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert, Databricks ML Professional, Databricks Data Engineer Professional) are a plus.