Artificial Intelligence Expert

Job Overview

The Ministry of Economy & Tourism seeks an Artificial Intelligence Expert to join its AI Department. This role is pivotal in deploying AI systems effectively, ethically, and at scale across ministry operations. The expert will bridge technical AI capabilities with vital business needs via human-centered supervision, governance frameworks, and ongoing optimization, combining advanced technical knowledge with business insight, stakeholder engagement, and change leadership to ensure sustainable AI solutions that deliver measurable value.

Core Responsibilities

• Define and manage requirements for AI-ready data, including training sets, operational inputs, and decision models, ensuring high standards of data quality and consistency.
• Create and oversee Human-in-the-Loop workflows that validate AI results prior to operational deployment.
• Continuously monitor AI model accuracy, confidence levels, and detect performance drift to uphold operational effectiveness and service continuity.
• Conduct testing and training of AI agents through feedback loops, prompt engineering, and supervised learning techniques.
• Develop and execute AI governance structures, ethical policies, and compliance protocols aligned with governmental regulations.
• Participate in risk-based classification of AI applications and implement proportional control measures accordingly.
• Lead vendor management and contract governance to ensure technical ownership, transparency, and prevent supplier monopolies.
• Identify and mitigate risks such as model biases, adversarial threats, data poisoning, and model degradation over time.
• Design and lead educational initiatives on AI awareness for developers, users, and stakeholders impacted by AI within the ministry.
• Guide multidisciplinary teams and foster collaboration among development, engineering, operations, and business units.
• Translate AI technical abilities and limitations into actionable, clear guidance to enable informed decision-making by leadership and stakeholders.
• Establish and monitor AI performance indicators including accuracy, confidence, acceptance rates, and drift metrics, and generate regular performance reports.
• Manage feedback mechanisms from AI users and operational teams to drive continuous enhancement of models and processes.
• Identify new AI use cases and suggest workflow and interface improvements to maximize organizational impact.
• Support enterprise-wide scaling through standardization, reusable tools, templates, and documentation of best practices for consistency and efficiency.
• Address employee resistance to AI adoption by aligning AI applications to team-specific needs, building trust, and encouraging openness to speed intelligent solution uptake.
• Establish knowledge-sharing networks and communities of practice for AI between government entities, promoting collaboration and best practice exchange among professionals.
• Validate AI outputs, detect exceptional or boundary cases, and apply informed human judgment for complex decisions to guarantee system reliability and precision.
• Perform additional duties assigned by the AI Department head related to this role.

Qualifications and Experience

• PhD in Computer Science, AI, Engineering, Statistics, or related fields with no required experience.
• Master’s degree in relevant fields (Computer Science, AI, Data Science, Engineering) with a minimum of 3 years relevant experience.
• Bachelor’s degree in Computer Science, AI, Computer Engineering, Statistics, or related disciplines with at least 7 years of relevant experience.

Professional Certifications

• Certified in AI and Machine Learning on cloud platforms such as Google Cloud Professional ML Engineer, AWS Machine Learning Specialty, or Microsoft Azure AI Engineer Associate.
• Certifications in Large Language Models and prompt engineering, e.g., DeepLearning.AI Generative AI or Prompt Engineering Specialization.
• Certification in AI governance and ethics like IAPP AI Governance Professional or ISO/IEC 42001 Lead Implementer.
• Data science and engineering certifications such as IBM Data Science Professional or Databricks Data Engineer Associate.
• AI operations and MLOps certifications including MLflow MLOps Certified, Kubeflow Practitioner, or DataRobot MLOps.
• Certifications addressing AI security and adversarial AI such as Certified AI Security Professional or OWASP AI Security.
• Project management and change leadership credentials like PMP, PRINCE2, or Prosci Change Management.
• Training in Human-in-the-Loop workflow design, AI model testing, and drift evaluation.
• Courses on AI data architecture, knowledge graphs, and data mapping.
• Training for AI model performance measurement involving accuracy metrics, confidence scores, and acceptance rates.
• Information security fundamentals and data protection training tailored for government AI environments.