Artificial Intelligence Expert

Job Purpose

Serve as an Artificial Intelligence (AI) expert within the Ministry's AI Department, responsible for ensuring the effective, ethical, and scalable deployment of AI systems across the Ministry's operations. This role bridges the gap between AI technical capabilities and critical business needs through human-centered oversight, AI governance, and continuous optimization. The position combines deep technical expertise with business knowledge, stakeholder management, and change leadership to ensure AI applications remain sustainable and deliver measurable organizational value.

Key Responsibilities

• Define and oversee AI-ready data requirements, including training datasets, operational input data, and decision models, while ensuring data quality, consistency, and integrity.

• Design and manage Human-in-the-Loop (HITL) workflows to validate AI outputs before operational deployment.

• Monitor AI model accuracy, confidence levels, and performance drift to maintain operational effectiveness and ensure service continuity.

• Test and train AI agents using feedback mechanisms, prompt engineering, and supervised learning protocols.

• Develop and implement AI governance frameworks, ethical guidelines, and compliance policies aligned with approved government regulations.

• Participate in classifying AI applications according to their risk and impact levels and establish proportionate control measures based on the level of risk.

• Lead vendor oversight and contract governance to ensure technical ownership, transparency, and prevent vendor lock-in.

• Identify and mitigate AI-related risks, including model bias, adversarial attacks, training data poisoning, and model performance degradation over time.

• Design and lead AI awareness and education programs for developers, end users, and stakeholders affected by AI implementations across the Ministry.

• Guide cross-functional teams and coordinate multidisciplinary collaboration among solution development, engineering, operations, and business teams.

• Translate the technical capabilities and limitations of AI systems into practical recommendations and clear guidance to support informed decision-making by management and stakeholders.

• Define and monitor AI model performance metrics, including accuracy rates, confidence scores, output acceptance rates, and model drift indicators, and prepare periodic performance reports.

• Manage feedback loops from AI users and operational teams to continuously improve AI models and business processes.

• Identify emerging AI use cases and recommend workflow and user interface enhancements to maximize organizational value.

• Support the enterprise-wide scaling of AI applications by standardizing practices, developing reusable templates and tools, and documenting best practices to ensure consistency and efficiency.

• Address employee resistance and hesitation toward AI adoption by aligning AI solutions with team-specific business needs, building trust, and promoting openness to accelerate the adoption of intelligent solutions.

• Build knowledge-sharing networks and AI communities of practice across government entities, fostering collaboration and the exchange of best practices among AI professionals.

• Validate AI model outputs, identify edge cases and exceptional scenarios, and apply sound human judgment in complex decision-making to ensure the reliability and accuracy of AI systems.

• Perform any other duties assigned by the Head of the AI Department within the scope of the role.

Qualifications & Experience

• PhD in Computer Science, Artificial Intelligence, Engineering, Statistics, or a related field (no experience required).

• Master's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field (minimum 3 years of relevant experience).

• Bachelor's Degree in Computer Science, Artificial Intelligence, Computer Engineering, Statistics, or a related field (minimum 7 years of relevant experience).

Professional Certifications

• Professional certification in Artificial Intelligence and Machine Learning on cloud platforms, such as Google Cloud Professional Machine Learning Engineer, AWS Machine Learning Specialty, or Microsoft Azure AI Engineer Associate.

• Certification in Large Language Models (LLMs) and Prompt Engineering, such as DeepLearning.AI Generative AI Specialization or Prompt Engineering Specialization.

• Certification in AI Governance and Ethics, such as IAPP AI Governance Professional (AIGP) or ISO/IEC 42001 Lead Implementer.

• Certification in Data Science and Data Engineering, such as IBM Data Science Professional Certificate or Databricks Data Engineer Associate.

• Certification in AI Operations (MLOps), such as MLflow MLOps Certified, Kubeflow Practitioner, or DataRobot MLOps.

• Certification in AI Security and Adversarial AI, such as Certified AI Security Professional or OWASP AI Security.

• Certification in Project Management and Change Leadership, such as PMP, PRINCE2, or Prosci Change Management.

• Training course in Human-in-the-Loop (HITL) workflow design, AI model testing, and model drift evaluation.

• Training course in AI data architecture, data mapping, and knowledge graphs.

• Training course in AI model performance measurement, including accuracy metrics, confidence scores, and output acceptance rates.

• Training course in information security fundamentals and data protection in government AI environments.