Aspire Manpower Services

Artificial Intelligence Engineer

Dubai, UAEPosted today

Salary
AED 12k–18k a month· est.
Job type
Full time
Level
Mid level
Field
AI & Machine Learning
Work mode
On site

About the role

About the Role About the Role Aspire Manpower Services is hiring an AI Specialist / AI Engineer for a government entity in Dubai. We are seeking a technically strong professional to support the design, evaluation, development and implementation of AI initiatives. The role covers the full AI project lifecycle, from identifying opportunities and developing proofs of concept to deployment, monitoring and continuous improvement. Responsibilities • Work with stakeholders to identify AI opportunities and define use cases, technical requirements, project scope and success measures. • Design and review AI solution architectures, data requirements, integrations, APIs and infrastructure dependencies. • Develop, configure and integrate solutions using Machine Learning, Generative AI, Large Language Models (LLMs) and AI agents. • Assess technical feasibility, data quality, infrastructure readiness and implementation risks. • Establish evaluation frameworks and testing criteria to assess performance, reliability, security, safety and bias. • Support proofs of concept and pilots, including technical setup, testing, troubleshooting and recommendations for further implementation. • Evaluate vendor proposals, technical architectures and solution capabilities to support build-versus-buy decisions. • Coordinate with technology teams to deploy solutions into production, including documentation, monitoring and operational handover. • Monitor deployed solutions and support optimization, retraining and ongoing lifecycle management. • Track technical milestones, dependencies, risks and deliverables across multiple AI initiatives. • Embed responsible AI, data privacy, cybersecurity, human oversight and governance requirements throughout delivery. Qualifications • Qualifications and Experience Bachelor’s degree in Artificial Intelligence, Computer Science, Data Science, Machine Learning, Software Engineering, Computer/Electrical Engineering, Mathematics, Statistics or a closely related technical field. • A master’s degree is preferred. • Minimum 5 years of relevant professional experience in AI, machine learning, data science, software engineering or related technology roles. • At least 2 years of hands-on AI/ML implementation experience. Required Skills • Required Skills Strong practical knowledge of AI/ML development, evaluation, integration and deployment. • Ability to translate business requirements into scalable, secure and reliable technical solutions. • Sound technical judgment in assessing architectures, vendor solutions and implementation risks. • Strong problem-solving, documentation, communication and stakeholder coordination skills. • Ability to collaborate with business owners, technology teams, cybersecurity specialists, data stakeholders and external vendors. How to Apply How to Apply Apply through LinkedIn with your updated CV, highlighting your hands-on AI/ML experience and relevant project delivery achievements.

Responsibilities

  • Work with stakeholders to identify AI opportunities and define use cases, technical requirements, project scope and success measures.
  • Design and review AI solution architectures, data requirements, integrations, APIs and infrastructure dependencies.
  • Develop, configure and integrate solutions using Machine Learning, Generative AI, Large Language Models (LLMs) and AI agents.
  • Assess technical feasibility, data quality, infrastructure readiness and implementation risks.
  • Establish evaluation frameworks and testing criteria to assess performance, reliability, security, safety and bias.
  • Support proofs of concept and pilots, including technical setup, testing, troubleshooting and recommendations for further implementation.
  • Evaluate vendor proposals, technical architectures and solution capabilities to support build-versus-buy decisions.
  • Coordinate with technology teams to deploy solutions into production, including documentation, monitoring and operational handover.
  • Monitor deployed solutions and support optimization, retraining and ongoing lifecycle management.
  • Track technical milestones, dependencies, risks and deliverables across multiple AI initiatives.
  • Embed responsible AI, data privacy, cybersecurity, human oversight and governance requirements throughout delivery.

Skills

  • AI/ML development
  • AI/ML evaluation
  • AI/ML integration
  • AI deployment
  • data requirements
  • architectural design
  • generative AI
  • large language models (LLMs)
  • AI agents
  • vendor assessment
  • security and governance
  • cybersecurity considerations
  • documentation
  • stakeholder coordination
  • proofs of concept

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